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I implement a simple PCA wrapper for easy transform of vectors by PCA for example LabeledPoint or another complicated structure.
Example of usage:
```
import org.apache.spark.mllib.regression.LinearRegressionWithSGD
import org.apache.spark.mllib.regression.LabeledPoint
import org.apache.spark.mllib.linalg.Vectors
import org.apache.spark.mllib.feature.PCA
val data = sc.textFile("data/mllib/ridge-data/lpsa.data").map { line =>
val parts = line.split(',')
LabeledPoint(parts(0).toDouble, Vectors.dense(parts(1).split(' ').map(_.toDouble)))
}.cache()
val splits = data.randomSplit(Array(0.6, 0.4), seed = 11L)
val training = splits(0).cache()
val test = splits(1)
val pca = PCA.create(training.first().features.size/2, data.map(_.features))
val training_pca = training.map(p => p.copy(features = pca.transform(p.features)))
val test_pca = test.map(p => p.copy(features = pca.transform(p.features)))
val numIterations = 100
val model = LinearRegressionWithSGD.train(training, numIterations)
val model_pca = LinearRegressionWithSGD.train(training_pca, numIterations)
val valuesAndPreds = test.map { point =>
val score = model.predict(point.features)
(score, point.label)
}
val valuesAndPreds_pca = test_pca.map { point =>
val score = model_pca.predict(point.features)
(score, point.label)
}
val MSE = valuesAndPreds.map{case(v, p) => math.pow((v - p), 2)}.mean()
val MSE_pca = valuesAndPreds_pca.map{case(v, p) => math.pow((v - p), 2)}.mean()
println("Mean Squared Error = " + MSE)
println("PCA Mean Squared Error = " + MSE_pca)
```
Author: Kirill A. Korinskiy <catap@catap.ru>
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #4304 from catap/pca and squashes the following commits:
501bcd9 [Joseph K. Bradley] Small updates: removed k from Java-friendly PCA fit(). In PCASuite, converted results to set for comparison. Added an error message for bad k in PCA.
9dcc02b [Kirill A. Korinskiy] [SPARK-5521] fix scala style
1892a06 [Kirill A. Korinskiy] [SPARK-5521] PCA wrapper for easy transform vectors
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HT to Diana, just proposing an implementation of her suggestion, which I rather agreed with. Is there a second/third for the motion?
Refer to "self-contained" rather than "standalone" apps to avoid confusion with standalone deployment mode. And fix placement of reference to this in MLlib docs.
Author: Sean Owen <sowen@cloudera.com>
Closes #2787 from srowen/SPARK-1307 and squashes the following commits:
b5b82e2 [Sean Owen] Refer to "self-contained" rather than "standalone" apps to avoid confusion with standalone deployment mode. And fix placement of reference to this in MLlib docs.
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1. renamed mllib-basics to mllib-data-types
1. renamed mllib-stats to mllib-statistics
1. moved random data generation to the bottom of mllib-stats
1. updated toc accordingly
atalwalkar
Author: Xiangrui Meng <meng@databricks.com>
Closes #2151 from mengxr/mllib-doc-1.1 and squashes the following commits:
0bd79f3 [Xiangrui Meng] add mllib-data-types
b64a5d7 [Xiangrui Meng] update the content list of basis statistics in mllib-guide
f625cc2 [Xiangrui Meng] move mllib-basics to mllib-data-types
4d69250 [Xiangrui Meng] move random data generation to the bottom of statistics
e64f3ce [Xiangrui Meng] move mllib-stats.md to mllib-statistics.md
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Update the documentation to reflect the fact we can handle roughly square matrices.
Author: Reza Zadeh <rizlar@gmail.com>
Closes #2070 from rezazadeh/svddocs and squashes the following commits:
826b8fe [Reza Zadeh] left singular vectors
3f34fc6 [Reza Zadeh] PCA is still TS
7ffa2aa [Reza Zadeh] better title
aeaf39d [Reza Zadeh] More docs
788ed13 [Reza Zadeh] add computational cost explanation
6429c59 [Reza Zadeh] Add link to rowmatrix docs
1eeab8b [Reza Zadeh] Update SVD documentation to reflect roughly square
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As per discussions with Xiangrui, I've reorganized and edited the mllib documentation.
Author: Ameet Talwalkar <atalwalkar@gmail.com>
Closes #1908 from atalwalkar/master and squashes the following commits:
fe6938a [Ameet Talwalkar] made xiangruis suggested changes
840028b [Ameet Talwalkar] made xiangruis suggested changes
7ec366a [Ameet Talwalkar] reorganize and edit mllib documentation
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Standalone application examples are added to 'mllib-linear-methods.md' file written in Java.
This commit is related to the issue [Add full Java Examples in MLlib docs](https://issues.apache.org/jira/browse/SPARK-1945).
Also I changed the name of the sigmoid function from 'logit' to 'f'. This is because the logit function
is the inverse of sigmoid.
Thanks,
Michael
Author: Michael Giannakopoulos <miccagiann@gmail.com>
Closes #1311 from miccagiann/master and squashes the following commits:
8ffe5ab [Michael Giannakopoulos] Update code so as to comply with code standards.
f7ad5cc [Michael Giannakopoulos] Merge remote-tracking branch 'upstream/master'
38d92c7 [Michael Giannakopoulos] Adding PCA, SVD and LBFGS examples in Java. Performing minor updates in the already committed examples so as to eradicate the call of 'productElement' function whenever is possible.
cc0a089 [Michael Giannakopoulos] Modyfied Java examples so as to comply with coding standards.
b1141b2 [Michael Giannakopoulos] Added Java examples for Clustering and Collaborative Filtering [mllib-clustering.md & mllib-collaborative-filtering.md].
837f7a8 [Michael Giannakopoulos] Merge remote-tracking branch 'upstream/master'
15f0eb4 [Michael Giannakopoulos] Java examples included in 'mllib-linear-methods.md' file.
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Some improvements to MLlib guide:
1. [SPARK-1872] Update API links for unidoc.
2. [SPARK-1783] Added `page.displayTitle` to the global layout. If it is defined, use it instead of `page.title` for title display.
3. Add more Java/Python examples.
Author: Xiangrui Meng <meng@databricks.com>
Closes #816 from mengxr/mllib-doc and squashes the following commits:
ec2e407 [Xiangrui Meng] format scala example for ALS
cd9f40b [Xiangrui Meng] add a paragraph to summarize distributed matrix types
4617f04 [Xiangrui Meng] add python example to loadLibSVMFile and fix Java example
d6509c2 [Xiangrui Meng] [SPARK-1783] update mllib titles
561fdc0 [Xiangrui Meng] add a displayTitle option to global layout
195d06f [Xiangrui Meng] add Java example for summary stats and minor fix
9f1ff89 [Xiangrui Meng] update java api links in mllib-basics
7dad18e [Xiangrui Meng] update java api links in NB
3a0f4a6 [Xiangrui Meng] api/pyspark -> api/python
35bdeb9 [Xiangrui Meng] api/mllib -> api/scala
e4afaa8 [Xiangrui Meng] explicity state what might change
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(primarly) MLlib docs
While play-testing the Scala and Java code examples in the MLlib docs, I noticed a number of small compile errors, and some typos. This led to finding and fixing a few similar items in other docs.
Then in the course of building the site docs to check the result, I found a few small suggestions for the build instructions. I also found a few more formatting and markdown issues uncovered when I accidentally used maruku instead of kramdown.
Author: Sean Owen <sowen@cloudera.com>
Closes #653 from srowen/SPARK-1727 and squashes the following commits:
6e7c38a [Sean Owen] Final doc updates - one more compile error, and use of mean instead of sum and count
8f5e847 [Sean Owen] Fix markdown syntax issues that maruku flags, even though we use kramdown (but only those that do not affect kramdown's output)
99966a9 [Sean Owen] Update issue tracker URL in docs
23c9ac3 [Sean Owen] Add Scala Naive Bayes example, to use existing example data file (whose format needed a tweak)
8c81982 [Sean Owen] Fix small compile errors and typos across MLlib docs
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Preview: http://54.82.240.23:4000/mllib-guide.html
Table of contents:
* Basics
* Data types
* Summary statistics
* Classification and regression
* linear support vector machine (SVM)
* logistic regression
* linear linear squares, Lasso, and ridge regression
* decision tree
* naive Bayes
* Collaborative Filtering
* alternating least squares (ALS)
* Clustering
* k-means
* Dimensionality reduction
* singular value decomposition (SVD)
* principal component analysis (PCA)
* Optimization
* stochastic gradient descent
* limited-memory BFGS (L-BFGS)
Author: Xiangrui Meng <meng@databricks.com>
Closes #422 from mengxr/mllib-doc and squashes the following commits:
944e3a9 [Xiangrui Meng] merge master
f9fda28 [Xiangrui Meng] minor
9474065 [Xiangrui Meng] add alpha to ALS examples
928e630 [Xiangrui Meng] initialization_mode -> initializationMode
5bbff49 [Xiangrui Meng] add imports to labeled point examples
c17440d [Xiangrui Meng] fix python nb example
28f40dc [Xiangrui Meng] remove localhost:4000
369a4d3 [Xiangrui Meng] Merge branch 'master' into mllib-doc
7dc95cc [Xiangrui Meng] update linear methods
053ad8a [Xiangrui Meng] add links to go back to the main page
abbbf7e [Xiangrui Meng] update ALS argument names
648283e [Xiangrui Meng] level down statistics
14e2287 [Xiangrui Meng] add sample libsvm data and use it in guide
8cd2441 [Xiangrui Meng] minor updates
186ab07 [Xiangrui Meng] update section names
6568d65 [Xiangrui Meng] update toc, level up lr and svm
162ee12 [Xiangrui Meng] rename section names
5c1e1b1 [Xiangrui Meng] minor
8aeaba1 [Xiangrui Meng] wrap long lines
6ce6a6f [Xiangrui Meng] add summary statistics to toc
5760045 [Xiangrui Meng] claim beta
cc604bf [Xiangrui Meng] remove classification and regression
92747b3 [Xiangrui Meng] make section titles consistent
e605dd6 [Xiangrui Meng] add LIBSVM loader
f639674 [Xiangrui Meng] add python section to migration guide
c82ffb4 [Xiangrui Meng] clean optimization
31660eb [Xiangrui Meng] update linear algebra and stat
0a40837 [Xiangrui Meng] first pass over linear methods
1fc8271 [Xiangrui Meng] update toc
906ed0a [Xiangrui Meng] add a python example to naive bayes
5f0a700 [Xiangrui Meng] update collaborative filtering
656d416 [Xiangrui Meng] update mllib-clustering
86e143a [Xiangrui Meng] remove data types section from main page
8d1a128 [Xiangrui Meng] move part of linear algebra to data types and add Java/Python examples
d1b5cbf [Xiangrui Meng] merge master
72e4804 [Xiangrui Meng] one pass over tree guide
64f8995 [Xiangrui Meng] move decision tree guide to a separate file
9fca001 [Xiangrui Meng] add first version of linear algebra guide
53c9552 [Xiangrui Meng] update dependencies
f316ec2 [Xiangrui Meng] add migration guide
f399f6c [Xiangrui Meng] move linear-algebra to dimensionality-reduction
182460f [Xiangrui Meng] add guide for naive Bayes
137fd1d [Xiangrui Meng] re-organize toc
a61e434 [Xiangrui Meng] update mllib's toc
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