Skip to content

Instantly share code, notes, and snippets.

Mathieu Blondel mblondel

Block or report user

Report or block mblondel

Hide content and notifications from this user.

Learn more about blocking users

Contact Support about this user’s behavior.

Learn more about reporting abuse

Report abuse
View GitHub Profile
View multiclass_svm.py
"""
Multiclass SVMs (Crammer-Singer formulation).
A pure Python re-implementation of:
Large-scale Multiclass Support Vector Machine Training via Euclidean Projection onto the Simplex.
Mathieu Blondel, Akinori Fujino, and Naonori Ueda.
ICPR 2014.
http://www.mblondel.org/publications/mblondel-icpr2014.pdf
"""
@mblondel
mblondel / letor_metrics.py
Last active Jan 19, 2020
Learning to rank metrics.
View letor_metrics.py
# (C) Mathieu Blondel, November 2013
# License: BSD 3 clause
import numpy as np
def ranking_precision_score(y_true, y_score, k=10):
"""Precision at rank k
Parameters
@mblondel
mblondel / check_convex.py
Last active Jan 14, 2020
A small script to get numerical evidence that a function is convex
View check_convex.py
# Authors: Mathieu Blondel, Vlad Niculae
# License: BSD 3 clause
import numpy as np
def _gen_pairs(gen, max_iter, max_inner, random_state, verbose):
rng = np.random.RandomState(random_state)
# if tuple, interpret as randn
@mblondel
mblondel / svm.py
Last active Jan 7, 2020
Support Vector Machines
View svm.py
# Mathieu Blondel, September 2010
# License: BSD 3 clause
import numpy as np
from numpy import linalg
import cvxopt
import cvxopt.solvers
def linear_kernel(x1, x2):
return np.dot(x1, x2)
@mblondel
mblondel / lda_gibbs.py
Last active Nov 30, 2019
Latent Dirichlet Allocation with Gibbs sampler
View lda_gibbs.py
"""
(C) Mathieu Blondel - 2010
License: BSD 3 clause
Implementation of the collapsed Gibbs sampler for
Latent Dirichlet Allocation, as described in
Finding scientifc topics (Griffiths and Steyvers)
"""
View kernel_kmeans.py
"""Kernel K-means"""
# Author: Mathieu Blondel <mathieu@mblondel.org>
# License: BSD 3 clause
import numpy as np
from sklearn.base import BaseEstimator, ClusterMixin
from sklearn.metrics.pairwise import pairwise_kernels
from sklearn.utils import check_random_state
@mblondel
mblondel / projection_simplex_isotonic.py
Created Nov 2, 2019
Projection onto the probability simplex using isotonic regression.
View projection_simplex_isotonic.py
# Author: Mathieu Blondel
# License: BSD 3 clause
import numpy as np
from sklearn.isotonic import isotonic_regression
def projection_simplex(x, z=1):
"""
Compute argmin_{p : p >= 0 and \sum_i p_i = z} ||p - x||
@mblondel
mblondel / projection_simplex_vectorized.py
Last active Nov 2, 2019
Vectorized projection onto the simplex
View projection_simplex_vectorized.py
# Author: Mathieu Blondel
# License: BSD 3 clause
import numpy as np
def projection_simplex(V, z=1, axis=None):
"""
Projection of x onto the simplex, scaled by z:
P(x; z) = argmin_{y >= 0, sum(y) = z} ||y - x||^2
@mblondel
mblondel / seminb.py
Created Oct 28, 2015
Semi-supervised Naive Bayes
View seminb.py
# -*- coding: utf-8 -*-
# Copyright (C) 2010 Mathieu Blondel
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
@mblondel
mblondel / statistical_tests.py
Last active Oct 19, 2019
t-test and wilcoxon-test examples in Python
View statistical_tests.py
# Mathieu Blondel, February 2012
# License: BSD 3 clause
# Port to Python of examples in chapter 5 of
# "Introductory Statistics with R" by Peter Dalgaard
import numpy as np
from scipy.stats import ttest_1samp, wilcoxon, ttest_ind, mannwhitneyu
# daily intake of energy in kJ for 11 women
You can’t perform that action at this time.