Updated anomaly detection exporter examples

SoftwareAG · Nov 16, 2018 · 7578097 · 7578097
1 parent 154913f
commit 7578097
Show file tree

Hide file tree

Showing 2 changed files with 8 additions and 101 deletions.
diff --git a/examples/skl/6_IsolationForest_model_to_PMML.ipynb b/examples/skl/6_IsolationForest_model_to_PMML.ipynb
@@ -6,45 +6,14 @@
    "source": [
     "# anomaly → PMML (using Nyoka) \n",
     "\n",
-    "### Exporter: Anomaly Detection models (OneClassSVM) \n",
+    "### Exporter: Anomaly Detection models (Isolation Forests) \n",
     "### Data Set used: iris\n",
     "\n",
     "### **STEPS**: \n",
-    "- Build the model using sklearn OneClassSVM\n",
+    "- Build the model using sklearn Isolation Forests\n",
     "- Build PMML (Data Dictionary, Mining schema, Ouput, PMML) using Nyoka classes"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2018-07-10T06:27:56.864880Z",
-     "start_time": "2018-07-10T06:27:56.839880Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<style>.container { width:100% !important; }</style>"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Jupyter cells: 100% width \n",
-    "from IPython.core.display import display, HTML\n",
-    "display(HTML(\"<style>.container { width:100% !important; }</style>\"))\n",
-    "%config NotebookApp.iopub_data_rate_limit = 7000000000000.0 \n",
-    "%config NotebookApp.rate_limit_window=60.0"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -54,18 +23,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "from sklearn.ensemble import IsolationForest"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 1,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2018-07-10T06:27:59.647880Z",
@@ -80,18 +38,6 @@
       "\n",
       " Anomaly detection model is built successfully.\n"
      ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\swsh\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\sklearn\\utils\\deprecation.py:58: DeprecationWarning: Class Imputer is deprecated; Imputer was deprecated in version 0.20 and will be removed in 0.22. Import impute.SimpleImputer from sklearn instead.\n",
-      "  warnings.warn(msg, category=DeprecationWarning)\n",
-      "C:\\Users\\swsh\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\sklearn\\ensemble\\iforest.py:214: FutureWarning: default contamination parameter 0.1 will change in version 0.22 to \"auto\". This will change the predict method behavior.\n",
-      "  FutureWarning)\n",
-      "C:\\Users\\swsh\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\sklearn\\ensemble\\iforest.py:224: FutureWarning: behaviour=\"old\" is deprecated and will be removed in version 0.22. Please use behaviour=\"new\", which makes the decision_function change to match other anomaly detection algorithm API.\n",
-      "  FutureWarning)\n"
-     ]
     }
    ],
    "source": [
@@ -104,6 +50,7 @@
     "from sklearn import datasets\n",
     "from sklearn.pipeline import Pipeline\n",
     "from sklearn.preprocessing import StandardScaler, Imputer\n",
+    "from sklearn.ensemble import IsolationForest\n",
     "\n",
     "irisdata = datasets.load_iris()\n",
     "iris = pd.DataFrame(irisdata.data,columns=irisdata.feature_names)\n",
@@ -133,7 +80,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 2,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2018-07-10T06:28:05.359880Z",

diff --git a/examples/skl/7_OneClassSVM_Model_to_PMML.ipynb b/examples/skl/7_OneClassSVM_Model_to_PMML.ipynb
@@ -14,37 +14,6 @@
     "- Build PMML (Data Dictionary, Mining schema, Ouput, PMML) using Nyoka classes"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2018-07-10T06:27:56.864880Z",
-     "start_time": "2018-07-10T06:27:56.839880Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<style>.container { width:100% !important; }</style>"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Jupyter cells: 100% width \n",
-    "from IPython.core.display import display, HTML\n",
-    "display(HTML(\"<style>.container { width:100% !important; }</style>\"))\n",
-    "%config NotebookApp.iopub_data_rate_limit = 7000000000000.0 \n",
-    "%config NotebookApp.rate_limit_window=60.0"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -54,7 +23,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 1,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2018-07-10T06:27:59.647880Z",
@@ -69,14 +38,6 @@
       "\n",
       " Anomaly detection model is built successfully.\n"
      ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\swsh\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\sklearn\\utils\\deprecation.py:58: DeprecationWarning: Class Imputer is deprecated; Imputer was deprecated in version 0.20 and will be removed in 0.22. Import impute.SimpleImputer from sklearn instead.\n",
-      "  warnings.warn(msg, category=DeprecationWarning)\n"
-     ]
     }
    ],
    "source": [
@@ -119,13 +80,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 2,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2018-07-10T06:28:05.359880Z",
      "start_time": "2018-07-10T06:28:04.605880Z"
-    },
-    "collapsed": true
+    }
    },
    "outputs": [],
    "source": [