examples/estimator/classifier/BernoulliNB/java/basics_imported.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# sklearn-porter\n",
    "\n",
    "Repository: https:/nok/sklearn-porter\n",
    "\n",
    "## BernoulliNB\n",
    "\n",
    "Documentation: [sklearn.naive_bayes.BernoulliNB](http://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.BernoulliNB.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "((150, 4), (150,))\n"
     ]
    }
   ],
   "source": [
    "from sklearn.datasets import load_iris\n",
    "\n",
    "iris_data = load_iris()\n",
    "X = iris_data.data\n",
    "y = iris_data.target\n",
    "\n",
    "print(X.shape, y.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Train classifier:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BernoulliNB(alpha=1.0, binarize=0.0, class_prior=None, fit_prior=True)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.naive_bayes import BernoulliNB\n",
    "\n",
    "clf = BernoulliNB()\n",
    "clf.fit(X, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Transpile classifier:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "import java.io.File;\n",
      "import java.io.FileNotFoundException;\n",
      "import java.util.*;\n",
      "import com.google.gson.Gson;\n",
      "\n",
      "\n",
      "class BernoulliNB {\n",
      "\n",
      "    private class Classifier {\n",
      "        private double[] priors;\n",
      "        private double[][] negProbs;\n",
      "        private double[][] delProbs;\n",
      "    }\n",
      "\n",
      "    private Classifier clf;\n",
      "\n",
      "    public BernoulliNB(String file) throws FileNotFoundException {\n",
      "        String jsonStr = new Scanner(new File(file)).useDelimiter(\"\\\\Z\").next();\n",
      "        this.clf = new Gson().fromJson(jsonStr, Classifier.class);\n",
      "    }\n",
      "\n",
      "    public int predict(double[] features) {\n",
      "        int nClasses = this.clf.priors.length;\n",
      "        int nFeatures = this.clf.delProbs.length;\n",
      "\n",
      "        double[] jll = new double[nClasses];\n",
      "        for (int i = 0; i < nClasses; i++) {\n",
      "            double sum = 0.;\n",
      "            for (int j = 0; j < nFeatures; j++) {\n",
      "                sum += features[i] * this.clf.delProbs[j][i];\n",
      "            }\n",
      "            jll[i] = sum;\n",
      "        }\n",
      "        for (int i = 0; i < nClasses; i++) {\n",
      "            double sum = 0.;\n",
      "            for (int j = 0; j < nFeatures; j++) {\n",
      "                sum += this.clf.negProbs[i][j];\n",
      "            }\n",
      "            jll[i] += this.clf.priors[i] + sum;\n",
      "        }\n",
      "\n",
      "        int classIndex = 0;\n",
      "        for (int i = 0; i < nClasses; i++) {\n",
      "            classIndex = jll[i] > jll[classIndex] ? i : classIndex;\n",
      "        }\n",
      "        return classIndex;\n",
      "    }\n",
      "\n",
      "    public static void main(String[] args) throws FileNotFoundException {\n",
      "        if (args.length > 0 && args[0].endsWith(\".json\")) {\n",
      "\n",
      "            // Features:\n",
      "            double[] features = new double[args.length-1];\n",
      "            for (int i = 1, l = args.length; i < l; i++) {\n",
      "                features[i - 1] = Double.parseDouble(args[i]);\n",
      "            }\n",
      "\n",
      "            // Parameters:\n",
      "            String modelData = args[0];\n",
      "\n",
      "            // Estimators:\n",
      "            BernoulliNB clf = new BernoulliNB(modelData);\n",
      "\n",
      "            // Prediction:\n",
      "            int prediction = clf.predict(features);\n",
      "            System.out.println(prediction);\n",
      "\n",
      "        }\n",
      "    }\n",
      "}\n",
      "CPU times: user 1.06 ms, sys: 1.01 ms, total: 2.07 ms\n",
      "Wall time: 1.31 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "from sklearn_porter import Porter\n",
    "\n",
    "porter = Porter(clf)\n",
    "output = porter.export(export_data=True)\n",
    "\n",
    "print(output)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"priors\": [-1.09861228867, -1.09861228867, -1.09861228867], \"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]], \"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]]}"
     ]
    }
   ],
   "source": [
    "%%bash\n",
    "\n",
    "cat data.json"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hideOutput": false
   },
   "source": [
    "### Run classification in Java:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Save the transpiled estimator:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "with open('BernoulliNB.java', 'w') as f:\n",
    "    f.write(output)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Download the dependencies:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "--2017-12-02 16:22:33--  http://central.maven.org/maven2/com/google/code/gson/gson/2.8.2/gson-2.8.2.jar\n",
      "Resolving central.maven.org... 151.101.36.209\n",
      "Connecting to central.maven.org|151.101.36.209|:80... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 232932 (227K) [application/java-archive]\n",
      "Saving to: 'gson-2.8.2.jar'\n",
      "\n",
      "     0K .......... .......... .......... .......... .......... 21% 1.65M 0s\n",
      "    50K .......... .......... .......... .......... .......... 43% 2.75M 0s\n",
      "   100K .......... .......... .......... .......... .......... 65% 3.53M 0s\n",
      "   150K .......... .......... .......... .......... .......... 87% 1.77M 0s\n",
      "   200K .......... .......... .......                         100% 2.79M=0.1s\n",
      "\n",
      "2017-12-02 16:22:33 (2.26 MB/s) - 'gson-2.8.2.jar' saved [232932/232932]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%%bash\n",
    "\n",
    "wget http://central.maven.org/maven2/com/google/code/gson/gson/2.8.2/gson-2.8.2.jar"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compiling:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%%bash\n",
    "\n",
    "javac -cp .:gson-2.8.2.jar BernoulliNB.java"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Prediction:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2\n"
     ]
    }
   ],
   "source": [
    "%%bash\n",
    "\n",
    "java -cp .:gson-2.8.2.jar BernoulliNB data.json 1 2 3 4"
   ]
  }
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