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Posted to reviews@spark.apache.org by wangmiao1981 <gi...@git.apache.org> on 2017/05/27 07:31:24 UTC
[GitHub] spark pull request #18128: [SPARK-20906][SparkR]:Constrained Logistic Regres...
GitHub user wangmiao1981 opened a pull request:
https://github.com/apache/spark/pull/18128
[SPARK-20906][SparkR]:Constrained Logistic Regression for SparkR
## What changes were proposed in this pull request?
PR https://github.com/apache/spark/pull/17715 Added Constrained Logistic Regression for ML. We should add it to SparkR.
## How was this patch tested?
Add new unit tests.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/wangmiao1981/spark test
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/18128.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #18128
----
commit 1fc68f69ecce46c8d4c2bbd2d9aafdd042c27108
Author: wangmiao1981 <wm...@hotmail.com>
Date: 2017-05-27T06:27:04Z
add constraint logit
commit 7627ac9c093ba72afd586c3ea1e482238d29c3c3
Author: wangmiao1981 <wm...@hotmail.com>
Date: 2017-05-27T07:29:25Z
add unit test and doc
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[GitHub] spark pull request #18128: [SPARK-20906][SparkR]:Constrained Logistic Regres...
Posted by felixcheung <gi...@git.apache.org>.
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/18128#discussion_r122135628
--- Diff: R/pkg/R/mllib_classification.R ---
@@ -239,21 +253,64 @@ function(object, path, overwrite = FALSE) {
setMethod("spark.logit", signature(data = "SparkDataFrame", formula = "formula"),
function(data, formula, regParam = 0.0, elasticNetParam = 0.0, maxIter = 100,
tol = 1E-6, family = "auto", standardization = TRUE,
- thresholds = 0.5, weightCol = NULL, aggregationDepth = 2) {
+ thresholds = 0.5, weightCol = NULL, aggregationDepth = 2,
+ lowerBoundsOnCoefficients = NULL, upperBoundsOnCoefficients = NULL,
+ lowerBoundsOnIntercepts = NULL, upperBoundsOnIntercepts = NULL) {
formula <- paste(deparse(formula), collapse = "")
+ row <- 0
+ col <- 0
if (!is.null(weightCol) && weightCol == "") {
weightCol <- NULL
} else if (!is.null(weightCol)) {
weightCol <- as.character(weightCol)
}
+ if (!is.null(lowerBoundsOnIntercepts)) {
+ lowerBoundsOnIntercepts <- as.array(lowerBoundsOnIntercepts)
+ }
+
+ if (!is.null(upperBoundsOnIntercepts)) {
+ upperBoundsOnIntercepts <- as.array(upperBoundsOnIntercepts)
+ }
+
+ if (!is.null(lowerBoundsOnCoefficients)) {
+ if (class(lowerBoundsOnCoefficients) != "matrix") {
+ stop("lowerBoundsOnCoefficients must be a matrix.")
+ }
+ row <- nrow(lowerBoundsOnCoefficients)
+ col <- ncol(lowerBoundsOnCoefficients)
+ lowerBoundsOnCoefficients <- as.array(as.vector(lowerBoundsOnCoefficients))
+ }
+
+ if (!is.null(upperBoundsOnCoefficients)) {
+ if (class(upperBoundsOnCoefficients) != "matrix") {
+ stop("upperBoundsOnCoefficients must be a matrix.")
+ }
+
+ if (!is.null(lowerBoundsOnCoefficients) & (row != nrow(upperBoundsOnCoefficients)
+ | col != ncol(upperBoundsOnCoefficients))) {
--- End diff --
while logically and semantically correct here, might prefer `&&` and `||` instead of `&` and `|` here for programmability/correctness in case something becomes length > 1 here later
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/18128
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/18128
**[Test build #77607 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/77607/testReport)** for PR 18128 at commit [`4c7b97c`](https://github.com/apache/spark/commit/4c7b97c16ba0e89ba96283ee5a0a9ad489329b67).
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[GitHub] spark pull request #18128: [SPARK-20906][SparkR]:Constrained Logistic Regres...
Posted by wangmiao1981 <gi...@git.apache.org>.
Github user wangmiao1981 commented on a diff in the pull request:
https://github.com/apache/spark/pull/18128#discussion_r119911447
--- Diff: R/pkg/R/mllib_classification.R ---
@@ -239,21 +253,57 @@ function(object, path, overwrite = FALSE) {
setMethod("spark.logit", signature(data = "SparkDataFrame", formula = "formula"),
function(data, formula, regParam = 0.0, elasticNetParam = 0.0, maxIter = 100,
tol = 1E-6, family = "auto", standardization = TRUE,
- thresholds = 0.5, weightCol = NULL, aggregationDepth = 2) {
+ thresholds = 0.5, weightCol = NULL, aggregationDepth = 2,
+ lowerBoundsOnCoefficients = NULL, upperBoundsOnCoefficients = NULL,
+ lowerBoundsOnIntercepts = NULL, upperBoundsOnIntercepts = NULL) {
formula <- paste(deparse(formula), collapse = "")
+ lrow <- 0
+ lcol <- 0
+ urow <- 0
+ ucol <- 0
--- End diff --
Oh, I think I can do the check because I have a `NULL` check before enforcing the rule.
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/18128
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by yanboliang <gi...@git.apache.org>.
Github user yanboliang commented on the issue:
https://github.com/apache/spark/pull/18128
@wangmiao1981 I'm at DataWorks Summit today and tomorrow, will take a look by this Friday. Thanks.
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/18128
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/18128
**[Test build #77699 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/77699/testReport)** for PR 18128 at commit [`b89a0f7`](https://github.com/apache/spark/commit/b89a0f71d22b02b854ee0c4cad4656ae31fc0321).
* This patch **fails SparkR unit tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/18128
**[Test build #77706 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/77706/testReport)** for PR 18128 at commit [`2a7e6e3`](https://github.com/apache/spark/commit/2a7e6e3cde6431a6f2015c3ee731ed354934674d).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/18128
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[GitHub] spark pull request #18128: [SPARK-20906][SparkR]:Constrained Logistic Regres...
Posted by felixcheung <gi...@git.apache.org>.
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/18128#discussion_r118827649
--- Diff: R/pkg/R/mllib_classification.R ---
@@ -239,21 +253,51 @@ function(object, path, overwrite = FALSE) {
setMethod("spark.logit", signature(data = "SparkDataFrame", formula = "formula"),
function(data, formula, regParam = 0.0, elasticNetParam = 0.0, maxIter = 100,
tol = 1E-6, family = "auto", standardization = TRUE,
- thresholds = 0.5, weightCol = NULL, aggregationDepth = 2) {
+ thresholds = 0.5, weightCol = NULL, aggregationDepth = 2,
+ lowerBoundsOnCoefficients = NULL, upperBoundsOnCoefficients = NULL,
+ lowerBoundsOnIntercepts = NULL, upperBoundsOnIntercepts = NULL) {
formula <- paste(deparse(formula), collapse = "")
+ lrow <- 0
+ lcol <- 0
+ urow <- 0
+ ucol <- 0
if (!is.null(weightCol) && weightCol == "") {
weightCol <- NULL
} else if (!is.null(weightCol)) {
weightCol <- as.character(weightCol)
}
+ if (!is.null(lowerBoundsOnIntercepts)) {
+ lowerBoundsOnIntercepts <- as.array(lowerBoundsOnIntercepts)
+ }
+
+ if (!is.null(upperBoundsOnIntercepts)) {
+ upperBoundsOnIntercepts <- as.array(upperBoundsOnIntercepts)
+ }
+
+ if (!is.null(lowerBoundsOnCoefficients)) {
+ lrow <- nrow(lowerBoundsOnCoefficients)
+ lcol <- ncol(lowerBoundsOnCoefficients)
+ lowerBoundsOnCoefficients <- as.array(as.vector(lowerBoundsOnCoefficients))
+ }
+
+ if (!is.null(upperBoundsOnCoefficients)) {
+ urow <- nrow(upperBoundsOnCoefficients)
+ ucol <- ncol(upperBoundsOnCoefficients)
--- End diff --
could you add some check for upperBoundsOnCoefficients or lowerBoundsOnCoefficients
for example, if upperBoundsOnCoefficients is a vector instead of a matrix, ncol(as.array(upperBoundsOnCoefficients)) will be NA
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/18128
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/18128
**[Test build #77703 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/77703/testReport)** for PR 18128 at commit [`b89a0f7`](https://github.com/apache/spark/commit/b89a0f71d22b02b854ee0c4cad4656ae31fc0321).
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by felixcheung <gi...@git.apache.org>.
Github user felixcheung commented on the issue:
https://github.com/apache/spark/pull/18128
@yanboliang
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/18128
**[Test build #77462 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/77462/testReport)** for PR 18128 at commit [`354eeb3`](https://github.com/apache/spark/commit/354eeb3eeb54ae5ea53889026e3aaa90b218d277).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request #18128: [SPARK-20906][SparkR]:Constrained Logistic Regres...
Posted by asfgit <gi...@git.apache.org>.
Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/18128
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/18128
**[Test build #77695 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/77695/testReport)** for PR 18128 at commit [`47fbccc`](https://github.com/apache/spark/commit/47fbccc020827a8ccc06f53298b4c5344df43cd7).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/18128
**[Test build #77691 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/77691/testReport)** for PR 18128 at commit [`c304ba8`](https://github.com/apache/spark/commit/c304ba8c173da3d7c2c9d45a807d828d7074710e).
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by SparkQA <gi...@git.apache.org>.
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@wangmiao1981 Will review soon. Thanks.
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@yanboliang Can you take a look? Thanks!
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@felixcheung if I remove `as.integer`, backend doesn't recognize it as `integer`.
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[GitHub] spark pull request #18128: [SPARK-20906][SparkR]:Constrained Logistic Regres...
Posted by felixcheung <gi...@git.apache.org>.
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/18128#discussion_r122135013
--- Diff: R/pkg/R/mllib_classification.R ---
@@ -202,6 +202,20 @@ function(object, path, overwrite = FALSE) {
#' @param aggregationDepth The depth for treeAggregate (greater than or equal to 2). If the dimensions of features
#' or the number of partitions are large, this param could be adjusted to a larger size.
#' This is an expert parameter. Default value should be good for most cases.
+#' @param lowerBoundsOnCoefficients The lower bounds on coefficients if fitting under bound constrained optimization.
+#' The bound matrix must be compatible with the shape (1, number of features) for binomial
+#' regression, or (number of classes, number of features) for multinomial regression.
+#' It is a R matrix.
+#' @param upperBoundsOnCoefficients The upper bounds on coefficients if fitting under bound constrained optimization.
+#' The bound matrix must be compatible with the shape (1, number of features) for binomial
+#' regression, or (number of classes, number of features) for multinomial regression.
+#' It is a R matrix.
+#' @param lowerBoundsOnIntercepts The lower bounds on intercepts if fitting under bound constrained optimization.
+#' The bounds vector size must be equal with 1 for binomial regression, or the number
+#' of classes for multinomial regression.
+#' @param upperBoundsOnIntercepts The upper bounds on intercepts if fitting under bound constrained optimization.
+#' The bound vector size must be equal with 1 for binomial regression, or the number
--- End diff --
ditto here `size must be equal with 1`
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[GitHub] spark pull request #18128: [SPARK-20906][SparkR]:Constrained Logistic Regres...
Posted by wangmiao1981 <gi...@git.apache.org>.
Github user wangmiao1981 commented on a diff in the pull request:
https://github.com/apache/spark/pull/18128#discussion_r119978881
--- Diff: R/pkg/R/mllib_classification.R ---
@@ -239,21 +253,64 @@ function(object, path, overwrite = FALSE) {
setMethod("spark.logit", signature(data = "SparkDataFrame", formula = "formula"),
function(data, formula, regParam = 0.0, elasticNetParam = 0.0, maxIter = 100,
tol = 1E-6, family = "auto", standardization = TRUE,
- thresholds = 0.5, weightCol = NULL, aggregationDepth = 2) {
+ thresholds = 0.5, weightCol = NULL, aggregationDepth = 2,
+ lowerBoundsOnCoefficients = NULL, upperBoundsOnCoefficients = NULL,
+ lowerBoundsOnIntercepts = NULL, upperBoundsOnIntercepts = NULL) {
formula <- paste(deparse(formula), collapse = "")
+ row <- 0
+ col <- 0
if (!is.null(weightCol) && weightCol == "") {
weightCol <- NULL
} else if (!is.null(weightCol)) {
weightCol <- as.character(weightCol)
}
+ if (!is.null(lowerBoundsOnIntercepts)) {
+ lowerBoundsOnIntercepts <- as.array(lowerBoundsOnIntercepts)
+ }
+
+ if (!is.null(upperBoundsOnIntercepts)) {
+ upperBoundsOnIntercepts <- as.array(upperBoundsOnIntercepts)
+ }
+
+ if (!is.null(lowerBoundsOnCoefficients)) {
+ if (class(lowerBoundsOnCoefficients) != "matrix") {
+ stop("lowerBoundsOnCoefficients must be a matrix.")
+ }
+ row <- nrow(lowerBoundsOnCoefficients)
+ col <- ncol(lowerBoundsOnCoefficients)
+ lowerBoundsOnCoefficients <- as.array(as.vector(lowerBoundsOnCoefficients))
+ }
+
+ if (!is.null(upperBoundsOnCoefficients)) {
+ if (class(upperBoundsOnCoefficients) != "matrix") {
+ stop("upperBoundsOnCoefficients must be a matrix.")
+ }
+
+ if (!is.null(lowerBoundsOnCoefficients) & (row != nrow(upperBoundsOnCoefficients)
+ | col != ncol(upperBoundsOnCoefficients))) {
+ stop(paste("dimension of upperBoundsOnCoefficients ",
+ "is not the same as lowerBoundsOnCoefficients", sep = ""))
+ }
+
+ if (is.null(lowerBoundsOnCoefficients)) {
+ row <- nrow(upperBoundsOnCoefficients)
+ col <- ncol(upperBoundsOnCoefficients)
+ }
--- End diff --
This is the case where we only set the upperbound. We can set both or either one of them.
For the case that both are set. We enforce upperbound and lowerbound are the same dimension, as checked above.
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/18128
Merged build finished. Test PASSed.
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[GitHub] spark pull request #18128: [SPARK-20906][SparkR]:Constrained Logistic Regres...
Posted by felixcheung <gi...@git.apache.org>.
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/18128#discussion_r119978607
--- Diff: R/pkg/R/mllib_classification.R ---
@@ -239,21 +253,64 @@ function(object, path, overwrite = FALSE) {
setMethod("spark.logit", signature(data = "SparkDataFrame", formula = "formula"),
function(data, formula, regParam = 0.0, elasticNetParam = 0.0, maxIter = 100,
tol = 1E-6, family = "auto", standardization = TRUE,
- thresholds = 0.5, weightCol = NULL, aggregationDepth = 2) {
+ thresholds = 0.5, weightCol = NULL, aggregationDepth = 2,
+ lowerBoundsOnCoefficients = NULL, upperBoundsOnCoefficients = NULL,
+ lowerBoundsOnIntercepts = NULL, upperBoundsOnIntercepts = NULL) {
formula <- paste(deparse(formula), collapse = "")
+ row <- 0
+ col <- 0
if (!is.null(weightCol) && weightCol == "") {
weightCol <- NULL
} else if (!is.null(weightCol)) {
weightCol <- as.character(weightCol)
}
+ if (!is.null(lowerBoundsOnIntercepts)) {
+ lowerBoundsOnIntercepts <- as.array(lowerBoundsOnIntercepts)
+ }
+
+ if (!is.null(upperBoundsOnIntercepts)) {
+ upperBoundsOnIntercepts <- as.array(upperBoundsOnIntercepts)
+ }
+
+ if (!is.null(lowerBoundsOnCoefficients)) {
+ if (class(lowerBoundsOnCoefficients) != "matrix") {
+ stop("lowerBoundsOnCoefficients must be a matrix.")
+ }
+ row <- nrow(lowerBoundsOnCoefficients)
+ col <- ncol(lowerBoundsOnCoefficients)
+ lowerBoundsOnCoefficients <- as.array(as.vector(lowerBoundsOnCoefficients))
+ }
+
+ if (!is.null(upperBoundsOnCoefficients)) {
+ if (class(upperBoundsOnCoefficients) != "matrix") {
+ stop("upperBoundsOnCoefficients must be a matrix.")
+ }
+
+ if (!is.null(lowerBoundsOnCoefficients) & (row != nrow(upperBoundsOnCoefficients)
+ | col != ncol(upperBoundsOnCoefficients))) {
+ stop(paste("dimension of upperBoundsOnCoefficients ",
+ "is not the same as lowerBoundsOnCoefficients", sep = ""))
+ }
+
+ if (is.null(lowerBoundsOnCoefficients)) {
+ row <- nrow(upperBoundsOnCoefficients)
+ col <- ncol(upperBoundsOnCoefficients)
+ }
+
+ upperBoundsOnCoefficients <- as.array(as.vector(upperBoundsOnCoefficients))
+ }
+
jobj <- callJStatic("org.apache.spark.ml.r.LogisticRegressionWrapper", "fit",
data@sdf, formula, as.numeric(regParam),
as.numeric(elasticNetParam), as.integer(maxIter),
as.numeric(tol), as.character(family),
as.logical(standardization), as.array(thresholds),
- weightCol, as.integer(aggregationDepth))
+ weightCol, as.integer(aggregationDepth),
+ as.integer(row), as.integer(col),
--- End diff --
nit: no need to `as.integer(row)` and `as.integer(col)` since they are set internally and not a parameter
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[GitHub] spark pull request #18128: [SPARK-20906][SparkR]:Constrained Logistic Regres...
Posted by wangmiao1981 <gi...@git.apache.org>.
Github user wangmiao1981 commented on a diff in the pull request:
https://github.com/apache/spark/pull/18128#discussion_r119911006
--- Diff: R/pkg/R/mllib_classification.R ---
@@ -239,21 +253,57 @@ function(object, path, overwrite = FALSE) {
setMethod("spark.logit", signature(data = "SparkDataFrame", formula = "formula"),
function(data, formula, regParam = 0.0, elasticNetParam = 0.0, maxIter = 100,
tol = 1E-6, family = "auto", standardization = TRUE,
- thresholds = 0.5, weightCol = NULL, aggregationDepth = 2) {
+ thresholds = 0.5, weightCol = NULL, aggregationDepth = 2,
+ lowerBoundsOnCoefficients = NULL, upperBoundsOnCoefficients = NULL,
+ lowerBoundsOnIntercepts = NULL, upperBoundsOnIntercepts = NULL) {
formula <- paste(deparse(formula), collapse = "")
+ lrow <- 0
+ lcol <- 0
+ urow <- 0
+ ucol <- 0
--- End diff --
Question: Based on my understanding, `lowerBoundsOnCoefficients ` and `upperBoundsOnCoefficients ` are not required to set at the same time. They can be set at the same time.
For the first case, we can't enforce the dimension of the two matrices because one could be `NULL`.
For the second case, we can check it.
So, we can't enforce the rule in general.
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/18128
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by wangmiao1981 <gi...@git.apache.org>.
Github user wangmiao1981 commented on the issue:
https://github.com/apache/spark/pull/18128
ping @yanboliang
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/18128
**[Test build #77455 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/77455/testReport)** for PR 18128 at commit [`7627ac9`](https://github.com/apache/spark/commit/7627ac9c093ba72afd586c3ea1e482238d29c3c3).
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/18128
Merged build finished. Test FAILed.
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by wangmiao1981 <gi...@git.apache.org>.
Github user wangmiao1981 commented on the issue:
https://github.com/apache/spark/pull/18128
Jenkins retest this please
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by felixcheung <gi...@git.apache.org>.
Github user felixcheung commented on the issue:
https://github.com/apache/spark/pull/18128
ok, thanks, i guess it could be set as `0L` but this is good.
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/18128
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/18128
**[Test build #78172 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/78172/testReport)** for PR 18128 at commit [`45b62cc`](https://github.com/apache/spark/commit/45b62cc9b070105ff2553ffc7b1e5788dc8134e5).
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/18128
**[Test build #77699 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/77699/testReport)** for PR 18128 at commit [`b89a0f7`](https://github.com/apache/spark/commit/b89a0f71d22b02b854ee0c4cad4656ae31fc0321).
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/18128
**[Test build #77457 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/77457/testReport)** for PR 18128 at commit [`6a5b568`](https://github.com/apache/spark/commit/6a5b568fc3b3aae7b9524005b55bad6a14348bd6).
* This patch **fails SparkR unit tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request #18128: [SPARK-20906][SparkR]:Constrained Logistic Regres...
Posted by felixcheung <gi...@git.apache.org>.
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/18128#discussion_r119995950
--- Diff: R/pkg/R/mllib_classification.R ---
@@ -239,21 +253,64 @@ function(object, path, overwrite = FALSE) {
setMethod("spark.logit", signature(data = "SparkDataFrame", formula = "formula"),
function(data, formula, regParam = 0.0, elasticNetParam = 0.0, maxIter = 100,
tol = 1E-6, family = "auto", standardization = TRUE,
- thresholds = 0.5, weightCol = NULL, aggregationDepth = 2) {
+ thresholds = 0.5, weightCol = NULL, aggregationDepth = 2,
+ lowerBoundsOnCoefficients = NULL, upperBoundsOnCoefficients = NULL,
+ lowerBoundsOnIntercepts = NULL, upperBoundsOnIntercepts = NULL) {
formula <- paste(deparse(formula), collapse = "")
+ row <- 0
+ col <- 0
if (!is.null(weightCol) && weightCol == "") {
weightCol <- NULL
} else if (!is.null(weightCol)) {
weightCol <- as.character(weightCol)
}
+ if (!is.null(lowerBoundsOnIntercepts)) {
+ lowerBoundsOnIntercepts <- as.array(lowerBoundsOnIntercepts)
+ }
+
+ if (!is.null(upperBoundsOnIntercepts)) {
+ upperBoundsOnIntercepts <- as.array(upperBoundsOnIntercepts)
+ }
+
+ if (!is.null(lowerBoundsOnCoefficients)) {
+ if (class(lowerBoundsOnCoefficients) != "matrix") {
+ stop("lowerBoundsOnCoefficients must be a matrix.")
+ }
+ row <- nrow(lowerBoundsOnCoefficients)
+ col <- ncol(lowerBoundsOnCoefficients)
+ lowerBoundsOnCoefficients <- as.array(as.vector(lowerBoundsOnCoefficients))
+ }
+
+ if (!is.null(upperBoundsOnCoefficients)) {
+ if (class(upperBoundsOnCoefficients) != "matrix") {
+ stop("upperBoundsOnCoefficients must be a matrix.")
+ }
+
+ if (!is.null(lowerBoundsOnCoefficients) & (row != nrow(upperBoundsOnCoefficients)
+ | col != ncol(upperBoundsOnCoefficients))) {
+ stop(paste("dimension of upperBoundsOnCoefficients ",
+ "is not the same as lowerBoundsOnCoefficients", sep = ""))
+ }
+
+ if (is.null(lowerBoundsOnCoefficients)) {
+ row <- nrow(upperBoundsOnCoefficients)
+ col <- ncol(upperBoundsOnCoefficients)
+ }
--- End diff --
ok thanks, L290-291
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/18128
Merged build finished. Test PASSed.
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[GitHub] spark pull request #18128: [SPARK-20906][SparkR]:Constrained Logistic Regres...
Posted by yanboliang <gi...@git.apache.org>.
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/18128#discussion_r119787497
--- Diff: R/pkg/R/mllib_classification.R ---
@@ -239,21 +253,57 @@ function(object, path, overwrite = FALSE) {
setMethod("spark.logit", signature(data = "SparkDataFrame", formula = "formula"),
function(data, formula, regParam = 0.0, elasticNetParam = 0.0, maxIter = 100,
tol = 1E-6, family = "auto", standardization = TRUE,
- thresholds = 0.5, weightCol = NULL, aggregationDepth = 2) {
+ thresholds = 0.5, weightCol = NULL, aggregationDepth = 2,
+ lowerBoundsOnCoefficients = NULL, upperBoundsOnCoefficients = NULL,
+ lowerBoundsOnIntercepts = NULL, upperBoundsOnIntercepts = NULL) {
formula <- paste(deparse(formula), collapse = "")
+ lrow <- 0
+ lcol <- 0
+ urow <- 0
+ ucol <- 0
--- End diff --
Here we can reduce from four parameters to two: ```nrow``` and ```ncol```, since the matrix format of ```lowerBoundsOnCoefficients``` and ```upperBoundsOnCoefficients``` should be consistent. If the input doesn't confirm with this rule, we need to throw exception.
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/18128
**[Test build #77462 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/77462/testReport)** for PR 18128 at commit [`354eeb3`](https://github.com/apache/spark/commit/354eeb3eeb54ae5ea53889026e3aaa90b218d277).
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by wangmiao1981 <gi...@git.apache.org>.
Github user wangmiao1981 commented on the issue:
https://github.com/apache/spark/pull/18128
Local test passed. Let me check it tonight.
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/18128
**[Test build #77691 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/77691/testReport)** for PR 18128 at commit [`c304ba8`](https://github.com/apache/spark/commit/c304ba8c173da3d7c2c9d45a807d828d7074710e).
* This patch **fails R style tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request #18128: [SPARK-20906][SparkR]:Constrained Logistic Regres...
Posted by felixcheung <gi...@git.apache.org>.
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/18128#discussion_r119978589
--- Diff: R/pkg/R/mllib_classification.R ---
@@ -239,21 +253,64 @@ function(object, path, overwrite = FALSE) {
setMethod("spark.logit", signature(data = "SparkDataFrame", formula = "formula"),
function(data, formula, regParam = 0.0, elasticNetParam = 0.0, maxIter = 100,
tol = 1E-6, family = "auto", standardization = TRUE,
- thresholds = 0.5, weightCol = NULL, aggregationDepth = 2) {
+ thresholds = 0.5, weightCol = NULL, aggregationDepth = 2,
+ lowerBoundsOnCoefficients = NULL, upperBoundsOnCoefficients = NULL,
+ lowerBoundsOnIntercepts = NULL, upperBoundsOnIntercepts = NULL) {
formula <- paste(deparse(formula), collapse = "")
+ row <- 0
+ col <- 0
if (!is.null(weightCol) && weightCol == "") {
weightCol <- NULL
} else if (!is.null(weightCol)) {
weightCol <- as.character(weightCol)
}
+ if (!is.null(lowerBoundsOnIntercepts)) {
+ lowerBoundsOnIntercepts <- as.array(lowerBoundsOnIntercepts)
+ }
+
+ if (!is.null(upperBoundsOnIntercepts)) {
+ upperBoundsOnIntercepts <- as.array(upperBoundsOnIntercepts)
+ }
+
+ if (!is.null(lowerBoundsOnCoefficients)) {
+ if (class(lowerBoundsOnCoefficients) != "matrix") {
+ stop("lowerBoundsOnCoefficients must be a matrix.")
+ }
+ row <- nrow(lowerBoundsOnCoefficients)
+ col <- ncol(lowerBoundsOnCoefficients)
+ lowerBoundsOnCoefficients <- as.array(as.vector(lowerBoundsOnCoefficients))
+ }
+
+ if (!is.null(upperBoundsOnCoefficients)) {
+ if (class(upperBoundsOnCoefficients) != "matrix") {
+ stop("upperBoundsOnCoefficients must be a matrix.")
+ }
+
+ if (!is.null(lowerBoundsOnCoefficients) & (row != nrow(upperBoundsOnCoefficients)
+ | col != ncol(upperBoundsOnCoefficients))) {
+ stop(paste("dimension of upperBoundsOnCoefficients ",
--- End diff --
paste would insert space - use paste0 instead or just remove the space in the string to let it to add it
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[GitHub] spark pull request #18128: [SPARK-20906][SparkR]:Constrained Logistic Regres...
Posted by yanboliang <gi...@git.apache.org>.
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/18128#discussion_r119788169
--- Diff: mllib/src/main/scala/org/apache/spark/ml/r/LogisticRegressionWrapper.scala ---
@@ -97,7 +97,15 @@ private[r] object LogisticRegressionWrapper
standardization: Boolean,
thresholds: Array[Double],
weightCol: String,
- aggregationDepth: Int
+ aggregationDepth: Int,
+ lrow: Int,
+ lcol: Int,
+ urow: Int,
+ ucol: Int,
--- End diff --
See my comment above, we can merge the four parameters into two: ```numRowsOfBoundsOnCoefficients``` and ```numColsOfBoundsOnCoefficients```, please follow Scala naming convention.
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/18128
Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/77695/
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[GitHub] spark pull request #18128: [SPARK-20906][SparkR]:Constrained Logistic Regres...
Posted by felixcheung <gi...@git.apache.org>.
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/18128#discussion_r119978644
--- Diff: R/pkg/R/mllib_classification.R ---
@@ -239,21 +253,64 @@ function(object, path, overwrite = FALSE) {
setMethod("spark.logit", signature(data = "SparkDataFrame", formula = "formula"),
function(data, formula, regParam = 0.0, elasticNetParam = 0.0, maxIter = 100,
tol = 1E-6, family = "auto", standardization = TRUE,
- thresholds = 0.5, weightCol = NULL, aggregationDepth = 2) {
+ thresholds = 0.5, weightCol = NULL, aggregationDepth = 2,
+ lowerBoundsOnCoefficients = NULL, upperBoundsOnCoefficients = NULL,
+ lowerBoundsOnIntercepts = NULL, upperBoundsOnIntercepts = NULL) {
formula <- paste(deparse(formula), collapse = "")
+ row <- 0
+ col <- 0
if (!is.null(weightCol) && weightCol == "") {
weightCol <- NULL
} else if (!is.null(weightCol)) {
weightCol <- as.character(weightCol)
}
+ if (!is.null(lowerBoundsOnIntercepts)) {
+ lowerBoundsOnIntercepts <- as.array(lowerBoundsOnIntercepts)
+ }
+
+ if (!is.null(upperBoundsOnIntercepts)) {
+ upperBoundsOnIntercepts <- as.array(upperBoundsOnIntercepts)
+ }
+
+ if (!is.null(lowerBoundsOnCoefficients)) {
+ if (class(lowerBoundsOnCoefficients) != "matrix") {
+ stop("lowerBoundsOnCoefficients must be a matrix.")
+ }
+ row <- nrow(lowerBoundsOnCoefficients)
+ col <- ncol(lowerBoundsOnCoefficients)
+ lowerBoundsOnCoefficients <- as.array(as.vector(lowerBoundsOnCoefficients))
+ }
+
+ if (!is.null(upperBoundsOnCoefficients)) {
+ if (class(upperBoundsOnCoefficients) != "matrix") {
+ stop("upperBoundsOnCoefficients must be a matrix.")
+ }
+
+ if (!is.null(lowerBoundsOnCoefficients) & (row != nrow(upperBoundsOnCoefficients)
+ | col != ncol(upperBoundsOnCoefficients))) {
+ stop(paste("dimension of upperBoundsOnCoefficients ",
+ "is not the same as lowerBoundsOnCoefficients", sep = ""))
+ }
+
+ if (is.null(lowerBoundsOnCoefficients)) {
+ row <- nrow(upperBoundsOnCoefficients)
+ col <- ncol(upperBoundsOnCoefficients)
+ }
--- End diff --
given how this is used later in scala code, should there be a check that nrow(upper) == nrow(lower) and ditto for ncol(upper) == ncol(lower)?
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/18128
**[Test build #77703 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/77703/testReport)** for PR 18128 at commit [`b89a0f7`](https://github.com/apache/spark/commit/b89a0f71d22b02b854ee0c4cad4656ae31fc0321).
* This patch **fails SparkR unit tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request #18128: [SPARK-20906][SparkR]:Constrained Logistic Regres...
Posted by felixcheung <gi...@git.apache.org>.
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/18128#discussion_r122134992
--- Diff: R/pkg/R/mllib_classification.R ---
@@ -202,6 +202,20 @@ function(object, path, overwrite = FALSE) {
#' @param aggregationDepth The depth for treeAggregate (greater than or equal to 2). If the dimensions of features
#' or the number of partitions are large, this param could be adjusted to a larger size.
#' This is an expert parameter. Default value should be good for most cases.
+#' @param lowerBoundsOnCoefficients The lower bounds on coefficients if fitting under bound constrained optimization.
+#' The bound matrix must be compatible with the shape (1, number of features) for binomial
+#' regression, or (number of classes, number of features) for multinomial regression.
+#' It is a R matrix.
+#' @param upperBoundsOnCoefficients The upper bounds on coefficients if fitting under bound constrained optimization.
+#' The bound matrix must be compatible with the shape (1, number of features) for binomial
+#' regression, or (number of classes, number of features) for multinomial regression.
+#' It is a R matrix.
+#' @param lowerBoundsOnIntercepts The lower bounds on intercepts if fitting under bound constrained optimization.
+#' The bounds vector size must be equal with 1 for binomial regression, or the number
--- End diff --
`size must be equal with 1` - should this be `size must be equal to 1`?
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[GitHub] spark pull request #18128: [SPARK-20906][SparkR]:Constrained Logistic Regres...
Posted by yanboliang <gi...@git.apache.org>.
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/18128#discussion_r119788377
--- Diff: R/pkg/inst/tests/testthat/test_mllib_classification.R ---
@@ -225,6 +225,32 @@ test_that("spark.logit", {
model2 <- spark.logit(df2, label ~ feature, weightCol = "weight")
prediction2 <- collect(select(predict(model2, df2), "prediction"))
expect_equal(sort(prediction2$prediction), c("0.0", "0.0", "0.0", "0.0", "0.0"))
+
+ # Test binomial logistic regression againt two classes with upperBoundsOnCoefficients
+ # and upperBoundsOnIntercepts
+ u <- matrix(c(1.0, 0.0, 1.0, 0.0), nrow = 1, ncol = 4)
+ model <- spark.logit(training, Species ~ ., upperBoundsOnCoefficients = u,
+ upperBoundsOnIntercepts = 1.0)
+ summary <- summary(model)
+ coefsR <- c(-11.13331, 1.00000, 0.00000, 1.00000, 0.00000)
+ coefs <- summary$coefficients[, "Estimate"]
+ expect_true(all(abs(coefsR - coefs) < 0.1))
+ # Test upperBoundsOnCoefficients should be matrix
+ expect_error(spark.logit(training, Species ~ ., upperBoundsOnCoefficients = as.array(c(1, 2)),
+ upperBoundsOnIntercepts = 1.0))
+
+ # Test binomial logistic regression againt two classes with lowerBoundsOnCoefficients
+ # and lowerBoundsOnIntercepts
+ l <- matrix(c(0.0, -1.0, 0.0, -1.0), nrow = 1, ncol = 4)
+ model <- spark.logit(training, Species ~ ., lowerBoundsOnCoefficients = l,
+ lowerBoundsOnIntercepts = 0.0)
+ summary <- summary(model)
+ coefsR <- c(0, 0, -1, 0, 1.902192)
+ coefs <- summary$coefficients[, "Estimate"]
+ expect_true(all(abs(coefsR - coefs) < 0.1))
+ # Test lowerBoundsOnCoefficients should be matrix
+ expect_error(spark.logit(training, Species ~ ., lowerBoundsOnCoefficients = as.array(c(1, 2)),
+ lowerBoundsOnIntercepts = 0.0))
--- End diff --
Could you add test for ```multinomial``` logistic regression? I think only test one side bound is enough.
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[GitHub] spark issue #18128: [SPARK-20906][SparkR]:Constrained Logistic Regression fo...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/18128
**[Test build #77909 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/77909/testReport)** for PR 18128 at commit [`c3190b5`](https://github.com/apache/spark/commit/c3190b5b4701afeceec17bbaa7c4ef6f0239b2c8).
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