Add new templates, examples and tests for the BernoulliNB classifier

nok · Dec 2, 2017 · 7eae57d · 7eae57d
1 parent b68c5df
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diff --git a/changelog.md b/changelog.md
@@ -41,6 +41,7 @@ All notable changes to this project will be documented in this file.
  - `ensemble.ExtraTreesClassifier` [notebook](examples/estimator/classifier/ExtraTreesClassifier/java/basics_imported.ipynb) ([#9979a94](https:/nok/sklearn-porter/commit/9979a948f51fef527b792babe06103c2c0dd5db4))
  - `tree.DecisionTreeClassifier` [notebook](examples/estimator/classifier/DecisionTreeClassifier/java/basics_imported.ipynb) ([#9979a94](https:/nok/sklearn-porter/commit/9979a948f51fef527b792babe06103c2c0dd5db4))
  - `neighbors.KNeighborsClassifier` [notebook](examples/estimator/classifier/KNeighborsClassifier/java/basics_imported.ipynb) ([#1b81d3f](https:/nok/sklearn-porter/commit/1b81d3f0e9cbe52203bbfde4cf73df17eacf4fdd#diff-86bc174b477eabd59f582e0e2882dcb3R54))
+ - `naive_bayes.GaussianNB` [notebook](examples/estimator/classifier/GaussianNB/java/basics_imported.ipynb) ([#b68c5df](https:/nok/sklearn-porter/commit/b68c5df241fec0b654d919066dca0663d909bde1))
  - `neural_network.MLPClassifier` [notebook](examples/estimator/classifier/MLPClassifier/java/basics_imported.ipynb) ([#b988f57](https:/nok/sklearn-porter/commit/b988f575db10133d41b1c80773bfe814b7271900), [#d8ff774](https:/nok/sklearn-porter/commit/d8ff77400c20ce41e318403bb12d2d65eeb3d309))
  - JavaScript:
  - `ensemble.AdaBoostClassifier` [notebook](examples/estimator/classifier/AdaBoostClassifier/js/basics_imported.ipynb) ([#9fdcc49](https:/nok/sklearn-porter/commit/9fdcc49355617668c3bf451a8d5828880245a4ae), [#dd70ac7](https:/nok/sklearn-porter/commit/dd70ac7e63cecad9028e9dea32efb7e1d2e43237), [#2401fba](https:/nok/sklearn-porter/commit/2401fba9938880bf420de0253e489c22e7b040e4))

diff --git a/examples/estimator/classifier/BernoulliNB/java/basics.ipynb b/examples/estimator/classifier/BernoulliNB/java/basics.ipynb
@@ -82,7 +82,7 @@
  },
  {
  "cell_type": "code",
- "execution_count": 3,
+ "execution_count": 4,
  "metadata": {
  "scrolled": false
  },
@@ -140,9 +140,9 @@
  " }\n",
  "\n",
  " // Parameters:\n",
- " final double[] priors = {-1.0986122886681096, -1.0986122886681096, -1.0986122886681096};\n",
- " final double[][] negProbs = {{-3.9512437185814138, -3.9512437185814138, -3.9512437185814138, -3.9512437185814138}, {-3.9512437185814138, -3.9512437185814138, -3.9512437185814138, -3.9512437185814138}, {-3.9512437185814138, -3.9512437185814138, -3.9512437185814138, -3.9512437185814138}};\n",
- " final double[][] delProbs = {{3.931825632724312, 3.931825632724312, 3.931825632724312}, {3.931825632724312, 3.931825632724312, 3.931825632724312}, {3.931825632724312, 3.931825632724312, 3.931825632724312}, {3.931825632724312, 3.931825632724312, 3.931825632724312}};\n",
+ " final double[] priors = {-1.09861228867, -1.09861228867, -1.09861228867};\n",
+ " final double[][] negProbs = {{-3.95124371858, -3.95124371858, -3.95124371858, -3.95124371858}, {-3.95124371858, -3.95124371858, -3.95124371858, -3.95124371858}, {-3.95124371858, -3.95124371858, -3.95124371858, -3.95124371858}};\n",
+ " final double[][] delProbs = {{3.93182563272, 3.93182563272, 3.93182563272}, {3.93182563272, 3.93182563272, 3.93182563272}, {3.93182563272, 3.93182563272, 3.93182563272}, {3.93182563272, 3.93182563272, 3.93182563272}};\n",
  "\n",
  " // Prediction:\n",
  " BernoulliNB clf = new BernoulliNB(priors, negProbs, delProbs);\n",
@@ -151,18 +151,94 @@
  "\n",
  " }\n",
  " }\n",
- "}\n"
+ "}\n",
+ "CPU times: user 1.04 ms, sys: 722 µs, total: 1.76 ms\n",
+ "Wall time: 1.25 ms\n"
  ]
  }
  ],
  "source": [
+ "%%time\n",
+ "\n",
  "from sklearn_porter import Porter\n",
  "\n",
  "porter = Porter(clf)\n",
  "output = porter.export()\n",
  "\n",
  "print(output)"
  ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Run classification in Java:"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Save the transpiled estimator:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "with open('BernoulliNB.java', 'w') as f:\n",
+ " f.write(output)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Compiling:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "%%bash\n",
+ "\n",
+ "javac -cp . BernoulliNB.java"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Prediction:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "2\n"
+ ]
+ }
+ ],
+ "source": [
+ "%%bash\n",
+ "\n",
+ "java -cp . BernoulliNB 1 2 3 4"
+ ]
  }
  ],
  "metadata": {