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 ...
read moreThere are comments.
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 ...
read moreThere are comments.
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 ...There are comments.
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 ...
read moreThere are comments.
Page 1 / 1