From c01089af443c514116ce6036346bdd66c2a33ffb Mon Sep 17 00:00:00 2001
From: Baptiste Bauvin <baptiste.bauvin.1@ulaval.ca>
Date: Fri, 2 Feb 2018 18:04:12 +0100
Subject: [PATCH] Added some docs and refactored some
---
.gitignore | 1 +
ipynb/How to add a monoview classifier.ipynb | 100 +++++++++++++++++++
2 files changed, 101 insertions(+)
create mode 100644 ipynb/How to add a monoview classifier.ipynb
diff --git a/.gitignore b/.gitignore
index 452926b3..971508ca 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 00000000..ab2ebf32
--- /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
+}
--
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