Isotonic Regression

Category: misc
#isotonic regression #machine learning #Python #scikit-learn

My latest contribution for scikit-learn is an implementation of the isotonic regression model that I coded with Nelle Varoquaux and Alexandre Gramfort. This model finds the best least squares fit to a set of points, given the constraint that the fit must be a non-decreasing function. The example on the …

Memory plots with memory_profiler

Category: misc
#Python #memory #memory_profiler

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 …

Singular Value Decomposition in SciPy

Category: misc
#python #scipy #svd

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 …

Learning to rank with scikit-learn: the pairwise transform

Category: misc
#python #scikit-learn #ranking

This tutorial introduces the concept of pairwise preference used in most ranking problems. I'll use scikit-learn and for learning and matplotlib for visualization.

In the ranking setting, training data consists of lists of items with some order specified between items in each list. This order is typically induced by giving …

line-by-line memory usage of a Python program

Category: misc
#python #memory_profiler

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 …

Low rank approximation

Category: misc
#machine learning #python

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 …

qr_multiply function in scipy.linalg

Category: misc
#python #scipy

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 …

scikit-learn EuroScipy 2011 coding sprint -- day one

Category: misc
#scikit-learn #python

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 …

Smells like hacker spirit

Category: misc
#python #sklearn

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!