diogojc

#!/usr/bin/python


def combinations(S):
    """
    Generates every possible combination from a set of discrete variables

    Arguments
    ---------
    S: Cardinality of variable space. When S = [2, 3, 4] variables 1, 2 and

diogojc

import numpy as np
import matplotlib.pyplot as plt


def params(X):
    """
    Calculates the mean vector and covariance matrix for the given data.

    Arguments
    ---------

diogojc

import numpy as np
from scipy.optimize import fmin_cg


def cost(p, Y, R, alpha):
    """
    Calculates collaborative filtering cost function.

    Arguments

diogojc

#!/usr/bin/python
# -*- coding: utf-8 -*-

import numpy as np
import matplotlib.pyplot as plt


class RidgeRegressor(object):
    """
    Linear Least Squares Regression with Tikhonov regularization.

diogojc

import numpy as np

def powerLaw(y, x):
    """
    'When the frequency of an event varies as power of some attribute of that
    event the frequency is said to follow a power law.' (wikipedia)

    This is represented by the following equation, where c and alpha are
    constants:
    y = c . x ^ alpha

diogojc

import numpy as np
from scipy.sparse import csc_matrix

def pageRank(G, s = .85, maxerr = .001):
    """
    Computes the pagerank for each of the n states.

    Used in webpage ranking and text summarization using unweighted
    or weighted transitions respectively.