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Loss Functions for Ordinal regression

Category: misc
#machine learning #ordinal regression #loss function

Note: this post contains a fair amount of LaTeX, if you don't visualize the math correctly come to its original location

In machine learning it is common to formulate the classification task as a minimization problem over a given loss function. Given data input data $(x_1, ..., x_n)$ and associated labels …

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 0.9

Category: General, scikit-learn

Last week we released a new version of scikit-learn. The Changelog is particularly impressive, yet personally this release is important for other reasons. This will probably be my last release as a paid engineer. I'm starting a PhD next month, and although I plan to continue contributing to the project …

Reworked example gallery for scikit-learn

Category: scikit-learn

I've been working lately in improving the scikit-learn example gallery to show also a small thumbnail of the plotted result. Here is what the gallery looks like now:

And the real thing should be already displayed in the development-documentation. The next thing is to add a static image to those …

scikit-learn’s EuroScipy 2011 coding sprint -- day two

Category: General, Python, scikit-learn

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Today's coding sprint was a bit more crowded, with some notable scipy hackers such as Ralph Gommers, Stefan van der Walt, David Cournapeau or Fernando Perez from Ipython joining in. On what got done: - We merged Jake's new BallTree code. This is a pure Cython implementation of a nearest-neighbor …