diff --git a/.gitignore b/.gitignore
index 452926b31586873ed9d208ae6e5b2abc753a1855..971508ca2f5ae106aab3a444a535e6da1e51aac8 100644
--- a/.gitignore
+++ b/.gitignore
@@ -2,6 +2,7 @@ TODO
 *.pyc
 .idea/**
 ipynb/.ipynb_checkpoints/**
+docs/source/monomulti/.ipynb_checkpoints/**
 Results/**
 Data/**
 multiview_platform/MonoMultiviewClassifiers/Results/*
diff --git a/ipynb/How to add a monoview classifier.ipynb b/ipynb/How to add a monoview classifier.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..ab2ebf32638f312ffaab649247a722bd3336ddf2
--- /dev/null
+++ b/ipynb/How to add a monoview classifier.ipynb	
@@ -0,0 +1,100 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Monoview classifier framework"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## File addition"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "* In the `MonoviewClassifiers` package, you need to add a python module called after your monoview classifier (let's call it MOC for **MO**noview **C**lassifier)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## The `MOC.py` file"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this file, you need to add several functions forthe platform to be able to use your classifier, they are alllisted below :  "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### `canProbas`"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This function is just used to knowif the classifier can predict a probability for each label instead of just predicting the a label."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def canProbas():\n",
+    "    return True"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### `fit`"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This function returns a fitted sklearn classifier object"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}