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Posted to commits@hivemall.apache.org by my...@apache.org on 2017/07/18 05:52:51 UTC
incubator-hivemall git commit: Close #101: [HIVEMALL-108-3] Describe
generic predictors' auxiliary options in document
Repository: incubator-hivemall
Updated Branches:
refs/heads/master 7ec82a6a8 -> 11bd1f83e
Close #101: [HIVEMALL-108-3] Describe generic predictors' auxiliary options in document
Project: http://git-wip-us.apache.org/repos/asf/incubator-hivemall/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-hivemall/commit/11bd1f83
Tree: http://git-wip-us.apache.org/repos/asf/incubator-hivemall/tree/11bd1f83
Diff: http://git-wip-us.apache.org/repos/asf/incubator-hivemall/diff/11bd1f83
Branch: refs/heads/master
Commit: 11bd1f83e68a7fbd2e0cc7143303e35e32edf692
Parents: 7ec82a6
Author: Takuya Kitazawa <k....@gmail.com>
Authored: Tue Jul 18 14:52:37 2017 +0900
Committer: Makoto Yui <my...@apache.org>
Committed: Tue Jul 18 14:52:37 2017 +0900
----------------------------------------------------------------------
.../java/hivemall/common/ConversionState.java | 4 +--
docs/gitbook/misc/prediction.md | 32 +++++++++++++++-----
2 files changed, 27 insertions(+), 9 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/11bd1f83/core/src/main/java/hivemall/common/ConversionState.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/hivemall/common/ConversionState.java b/core/src/main/java/hivemall/common/ConversionState.java
index ff92241..7b5923f 100644
--- a/core/src/main/java/hivemall/common/ConversionState.java
+++ b/core/src/main/java/hivemall/common/ConversionState.java
@@ -81,7 +81,7 @@ public final class ConversionState {
return currLosses > prevLosses;
}
- public boolean isConverged(final long obserbedTrainingExamples) {
+ public boolean isConverged(final long observedTrainingExamples) {
if (conversionCheck == false) {
return false;
}
@@ -110,7 +110,7 @@ public final class ConversionState {
if (logger.isDebugEnabled()) {
logger.debug("Iteration #" + curIter + " [curLosses=" + currLosses
+ ", prevLosses=" + prevLosses + ", changeRate=" + changeRate
- + ", #trainingExamples=" + obserbedTrainingExamples + ']');
+ + ", #trainingExamples=" + observedTrainingExamples + ']');
}
this.readyToFinishIterations = false;
}
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/11bd1f83/docs/gitbook/misc/prediction.md
----------------------------------------------------------------------
diff --git a/docs/gitbook/misc/prediction.md b/docs/gitbook/misc/prediction.md
index 317d688..ee85e40 100644
--- a/docs/gitbook/misc/prediction.md
+++ b/docs/gitbook/misc/prediction.md
@@ -109,8 +109,8 @@ Below we list possible options for `train_regression` and `train_classifier`, an
- For `train_regression`
- SquaredLoss (synonym: squared)
- QuantileLoss (synonym: quantile)
- - EpsilonInsensitiveLoss (synonym: epsilon_intensitive)
- - SquaredEpsilonInsensitiveLoss (synonym: squared_epsilon_intensitive)
+ - EpsilonInsensitiveLoss (synonym: epsilon_insensitive)
+ - SquaredEpsilonInsensitiveLoss (synonym: squared_epsilon_insensitive)
- HuberLoss (synonym: huber)
- For `train_classifier`
- HingeLoss (synonym: hinge)
@@ -120,8 +120,8 @@ Below we list possible options for `train_regression` and `train_classifier`, an
- The following losses are mainly designed for regression but can sometimes be useful in classification as well:
- SquaredLoss (synonym: squared)
- QuantileLoss (synonym: quantile)
- - EpsilonInsensitiveLoss (synonym: epsilon_intensitive)
- - SquaredEpsilonInsensitiveLoss (synonym: squared_epsilon_intensitive)
+ - EpsilonInsensitiveLoss (synonym: epsilon_insensitive)
+ - SquaredEpsilonInsensitiveLoss (synonym: squared_epsilon_insensitive)
- HuberLoss (synonym: huber)
- Regularization function: `-reg`, `-regularization`
@@ -130,9 +130,9 @@ Below we list possible options for `train_regression` and `train_classifier`, an
- ElasticNet
- RDA
-Additionally, there are several variants of the SGD technique, and it is also configureable as:
+Additionally, there are several variants of the SGD technique, and it is also configurable as:
-- Optimizer `-opt`, `-optimizer`
+- Optimizer: `-opt`, `-optimizer`
- SGD
- AdaGrad
- AdaDelta
@@ -140,6 +140,24 @@ Additionally, there are several variants of the SGD technique, and it is also co
> #### Note
>
-> Option values are case insensitive and you can use `sgd` or `rda`, or `huberloss`.
+> Option values are case insensitive and you can use `sgd` or `rda`, or `huberloss` in lower-case letters.
+
+Furthermore, optimizer offers to set auxiliary options such as:
+
+- Number of iterations: `-iter`, `-iterations` [default: 10]
+ - Repeat optimizer's learning procedure more than once to diligently find better result.
+- Convergence rate: `-cv_rate`, `-convergence_rate` [default: 0.005]
+ - Define a stopping criterion for the iterative training.
+ - If the criterion is too small or too large, you may encounter over-fitting or under-fitting depending on value of `-iter` option.
+- Mini-batch size: `-mini_batch`, `-mini_batch_size` [default: 1]
+ - Instead of learning samples one-by-one, this option enables optimizer to utilize multiple samples at once to minimize the error function.
+ - Appropriate mini-batch size leads efficient training and effective prediction model.
+
+For details of available options, following queries might be helpful to list all of them:
+
+```sql
+select train_regression(array(), 0, '-help');
+select train_classifier(array(), 0, '-help');
+```
In practice, you can try different combinations of the options in order to achieve higher prediction accuracy.
\ No newline at end of file