Updated decision tree calc

Author: mGalarnyk

.DS_Store

@@ -2,11 +2,22 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 18,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'%.3f'"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "%matplotlib inline\n",
     "\n",
@@ -19,12 +30,16 @@
     "\n",
     "from sklearn.model_selection import train_test_split\n",
     "from sklearn import tree\n",
-    "from IPython.display import Image"
+    "from IPython.display import Image\n",
+    "\n",
+    "#np.set_printoptions(precision=3)\n",
+    "\n",
+    "%precision 3"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 19,
    "metadata": {
     "collapsed": true
    },
@@ -73,7 +88,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "$$IG(D_P,f)=I(D_p) - \\sum_{j=1}^{m}\\frac{N_j}{N}I(D_j)$$"
+    "$$\\huge D_p$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "$$\\huge IG(D_p,f)=I(D_p) - \\sum_{j=1}^{m}\\frac{N_j}{N}I(D_j)$$"
    ]
   },
   {
@@ -94,7 +116,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "$$IG(D_P,\\alpha)=I(D_p) - \\frac{N_{left}}{N}I(D_{left})- \\frac{N_{right}}{N}I(D_{right})$$"
+    "$$\\huge IG(D_p,f)=I(D_p) - \\frac{N_{left}}{N}I(D_{left})- \\frac{N_{right}}{N}I(D_{right})$$"
    ]
   },
   {
@@ -130,7 +152,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 20,
    "metadata": {
     "collapsed": false
    },
@@ -142,7 +164,7 @@
        "<IPython.core.display.Image object>"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -170,23 +192,23 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### Information for Parent Dataset"
+    "#### Information for Parent"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 21,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "0.6651785714285714"
+       "0.665"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -202,27 +224,20 @@
     "#### Information for Child Node (left)"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Pure node so no calculation needed"
-   ]
-  },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 22,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "0.0"
+       "0.000"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -240,18 +255,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 23,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "0.4967129291453616"
+       "0.497"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -298,6 +313,26 @@
     "Image(filename =  PATH[0] + \"/Graphviz_Dot_Examples/iris_depth1_entropy_decisionTree.png\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    " np.set_printoptions(precision=3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -316,7 +351,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### Information for Parent Dataset"
+    "#### Information for Parent"
    ]
   },
   {
@@ -338,7 +373,7 @@
     }
    ],
    "source": [
-    "-1 * ( ((38.0 / 112)* np.log2(38.0/112)) + ((40.0 / 112)* np.log2(40.0/112)) + ((34.0 / 112)* np.log2(34.0/112)))"
+    "-1*( ((38.0 / 112)* np.log2(38.0/112)) + ((40.0 / 112)* np.log2(40.0/112)) + ((34.0 / 112)* np.log2(34.0/112)) )"
    ]
   },
   {
@@ -367,7 +402,7 @@
     }
    ],
    "source": [
-    "-1 * ( ((38.0 / 38.0)* np.log2(38.0/38.0)) )"
+    "-1*(((38.0 / 38.0)* np.log2(38.0/38.0)))"
    ]
   },
   {
@@ -396,7 +431,7 @@
     }
    ],
    "source": [
-    "-1 * ( ((40.0 / 74.0)* np.log2(40.0/74.0)) + ((34.0 / 74.0)* np.log2(34.0/74.0)) )"
+    "-1*( ((40.0 / 74.0)* np.log2(40.0/74.0)) + ((34.0 / 74.0)* np.log2(34.0/74.0)) )"
    ]
   }
  ],