Updated anomaly detection exporter examples

SoftwareAG · Nov 15, 2018 · 154913f · 154913f
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diff --git a/examples/skl/6_IsolationForest_model_to_PMML.ipynb b/examples/skl/6_IsolationForest_model_to_PMML.ipynb
@@ -4,18 +4,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<div class=\"alert alert-block alert-info\">\n",
-    "# <font size = 30>anomaly → PMML (using Nyoka) </font>\n",
+    "# anomaly → PMML (using Nyoka) \n",
     "\n",
-    "<div class=\"alert alert-block alert-success\">\n",
-    "### <font color=purple> Exporter: Anomaly Detection models (OneClassSVM) </font>\n",
-    "### <font color=purple> Data Set used: iris </font>\n",
+    "### Exporter: Anomaly Detection models (OneClassSVM) \n",
+    "### Data Set used: iris\n",
     "\n",
-    "\n",
-    "### <font color=purple>**STEPS**: </font>\n",
-    "<font color=brown>\n",
+    "### **STEPS**: \n",
     "- Build the model using sklearn OneClassSVM\n",
-    "- Build PMML (Data Dictionary, Mining schema, Ouput, PMML) using Nyoka classes\n"
+    "- Build PMML (Data Dictionary, Mining schema, Ouput, PMML) using Nyoka classes"
    ]
   },
   {
@@ -53,7 +49,6 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<div class=\"alert alert-block alert-warning\">\n",
     "# Pre-processing, Model building (using pipeline) for iris data set"
    ]
   },
@@ -133,7 +128,6 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<div class=\"alert alert-block alert-warning\">\n",
     "# Export the Pipeline object into PMML using the Nyoka package"
    ]
   },
@@ -151,15 +145,6 @@
     "from nyoka import skl_to_pmml\n",
     "skl_to_pmml(pipeline=pipe, col_names=feature_names,target_name='Species', pmml_f_name=\"IsolationForest_model.pmml\")"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -178,7 +163,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.5"
   },
   "latex_envs": {
    "LaTeX_envs_menu_present": true,

diff --git a/examples/skl/7_OneClassSVM_Model_to_PMML.ipynb b/examples/skl/7_OneClassSVM_Model_to_PMML.ipynb
@@ -4,18 +4,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<div class=\"alert alert-block alert-info\">\n",
-    "# <font size = 30>anomaly → PMML (using Nyoka) </font>\n",
+    "# anomaly → PMML (using Nyoka)\n",
     "\n",
-    "<div class=\"alert alert-block alert-success\">\n",
-    "### <font color=purple> Exporter: Anomaly Detection models (OneClassSVM) </font>\n",
-    "### <font color=purple> Data Set used: iris </font>\n",
+    "### Exporter: Anomaly Detection models (OneClassSVM)\n",
+    "### Data Set used: iris \n",
     "\n",
-    "\n",
-    "### <font color=purple>**STEPS**: </font>\n",
-    "<font color=brown>\n",
+    "### **STEPS**: \n",
     "- Build the model using sklearn OneClassSVM\n",
-    "- Build PMML (Data Dictionary, Mining schema, Ouput, PMML) using Nyoka classes\n"
+    "- Build PMML (Data Dictionary, Mining schema, Ouput, PMML) using Nyoka classes"
    ]
   },
   {
@@ -53,7 +49,6 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<div class=\"alert alert-block alert-warning\">\n",
     "# Pre-processing, Model building (using pipeline) for iris data set"
    ]
   },
@@ -119,7 +114,6 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<div class=\"alert alert-block alert-warning\">\n",
     "# Export the Pipeline object into PMML using the Nyoka package"
    ]
   },
@@ -138,15 +132,6 @@
     "from nyoka import skl_to_pmml\n",
     "skl_to_pmml(pipeline=pipe, col_names=feature_names, pmml_f_name=\"OneClassSVM_model.pmml\")"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -165,7 +150,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.5"
   },
   "latex_envs": {
    "LaTeX_envs_menu_present": true,