Recently I've implemented, together with Arnaud Rachez, the SAGA[1] algorithm in the lightning machine learning library (which by the way, has been recently moved to the new scikit-learn-contrib project). The lightning library uses the same API as scikit-learn but is particularly adapted to online learning. As for the SAGA …
Cross-validation iterators in scikit-learn are simply generator objects, that is, Python objects that implement the __iter__ method and that for each call to this method return (or more precisely, yield) the indices or a boolean mask for the train and test set. Hence, implementing new cross-validation iterators that behave as …
Due to lack of time and interest, I'm no longer maintaining this project. Feel free to grab the sources from https://github.com/fabianp/nbgallery and fork the project.
TL;DR I created a gallery for IPython/Jupyter notebooks. Check it out :-)
A couple of months ago I put online …
Last Friday was PyData Paris, in words of the organizers, ''a gathering of users and developers of data analysis tools in Python''.
The organizers did a great job in putting together and the event started already with a full room for Gael's keynote
My take-away message from the talks is …
My latest research paper[1] deals with the estimation of the hemodynamic response function (HRF) from fMRI data.
This is an important topic since the knowledge of a hemodynamic response function is what makes it possible to extract the brain activation maps that are used in most of the impressive …
:og_image: http://fa.bianp.net/blog/images/2014/mprof_example.png
One of the lesser known features of the memory_profiler package is its ability to plot memory consumption as a function of time. This was implemented by my friend Philippe Gervais, previously a colleague at INRIA and now at Google.
With …
TL; DR These are some notes on calibration of surrogate loss functions in the context of machine learning. But mostly it is …
As part of the development of memory_profiler I've tried several ways to get memory usage of a program from within Python. In this post I'll describe the different alternatives I've tested.
psutil is a python library that provides an interface for retrieving information on running processes. It …
In this post I compar several implementations of Logistic Regression. The task was to implement a Logistic Regression model using standard optimization …
TL;DR: I've implemented a logistic ordinal regression or proportional odds model. Here is the Python code
The logistic ordinal regression model …
My latest contribution for scikit-learn is an implementation of the isotonic regression model that I coded with Nelle Varoquaux and Alexandre Gramfort …
Householder matrices are square matrices of the form
$$ P = I - \beta v v^T$$
where $\beta$ is a scalar and $v$ is …
Note: this post contains a fair amount of LaTeX, if you don't visualize the math correctly come to its original location
In …
Besides performing a line-by-line analysis of memory consumption,
memory_profiler
exposes some functions that allow to retrieve the memory consumption
of a function in real-time, allowing e.g. to visualize the memory
consumption of a given function over time.
The function to be used is memory_usage. The first argument
specifies what …
SciPy contains two methods to compute the singular value decomposition (SVD) of a matrix: scipy.linalg.svd and scipy.sparse.linalg.svds. In this post I'll compare both methods for the task of computing the full SVD of a large dense matrix.
The first method, scipy.linalg.svd, is perhaps …
This tutorial introduces the concept of pairwise preference used in most ranking problems. I'll use scikit-learn and for learning and matplotlib for …
My newest project is a Python library for monitoring memory consumption of arbitrary process, and one of its most useful features is the line-by-line analysis of memory usage for Python code. I wrote a basic prototype six months ago after being surprised by the lack of related tools. I wanted …
A little experiment to see what low rank approximation looks like. These are the best rank-k approximations (in the Frobenius norm) to the a natural image for increasing values of k and an original image of rank 512.
Python code can be found here. GIF animation made using ImageMagic's convert …
In scipy's development version there's a new function closely related to the QR-decomposition of a matrix and to the least-squares solution of a linear system. What this function does is to compute the QR-decomposition of a matrix and then multiply the resulting orthogonal factor by another arbitrary matrix. In pseudocode …
As a warm-up for the upcoming EuroScipy-conference, some of the scikit-learn developers decided to gather and work together for a couple of days. Today was the first day and there was only a handfull of us, as the real kickoff is expected tomorrow. Some interesting coding happened, although most of …
Ridge coefficients for multiple values of the regularization parameter can be elegantly computed by updating the thin SVD decomposition of the design matrix:
import numpy as np
from scipy import linalg
def ridge(A, b, alphas):
"""
Return coefficients for regularized least squares
min ||A x - b||^2 + alpha ||x||^2 …Update: a fast and stable norm was added to scipy.linalg in August 2011 and will be available in scipy 0.10 Last week I discussed with Gael how we should compute the euclidean norm of a vector a using SciPy. Two approaches suggest themselves, either calling scipy.linalg.norm …
I was last weekend in FOSDEM presenting scikits.learn (here are the slides I used at the Data Analytics Devroom). Kudos to Olivier Grisel and all the people who organized such a fun and authentic meeting!
I've been working lately with Alexandre Gramfort coding the LARS algorithm in scikits.learn. This algorithm computes the solution to several general linear models used in machine learning: LAR, Lasso, Elasticnet and Forward Stagewise. Unlike the implementation by coordinate descent, the LARS algorithm gives the full coefficient path along the …
En la ciudad fabrican a las personas en serie. En el campo, los siguen haciendo a mano: los moldean, los secan al sol y luego los pintan, por eso son tan especiales. Primer concierto de la nueva gira en Mengíbar, y uno de los fines de semana más intensos que …