returns the vector v (represented as a list) as a n x 1 matrix

returns the n x 1 matrix as a list of values

compute the vector whose i-th element is the mean of the i-th elements of the input vectors

Turn the word_counts into a list of triplets: w, p(w|spam) and p(w|~spam)

returns the num_columns x num_columns matrix whose (i, j)th entry is the correlation between columns i and j of data

the variance of the data in the direction w

1's on the 'diagonal', 0's everywhere else

returns 1 if the perceptron 'fires', 0 if not

Word Clouds

Random Forest Algorithm

finds the total squared error from k-means clustering the inputs

estimate error plus ridge penalty on beta

the gradient corresponding to the ith squared error term including the ridge penalty

returns the probability that a uniform random variable is less than x