| """ | |
| A bare bones examples of optimizing a black-box function (f) using | |
| Natural Evolution Strategies (NES), where the parameter distribution is a | |
| gaussian of fixed standard deviation. | |
| """ | |
| import numpy as np | |
| np.random.seed(0) | |
| # the function we want to optimize |
#IRC Reference
Not intended as a guide for newbies, more like a "cheat sheet" for the somewhat experienced IRC user, especially one who wields some power over a channel.
##The Basics
/join #channel
/part #channel
| def co_occurence_matrix(list_of_words, preprocessed_reviews, window_size=5): | |
| ''' | |
| Function which takes list of words and preprocessed_reviews as the inputs and | |
| returns the co_occurence_matrix. | |
| Args: | |
| list_of_words: A list of words for which the co-occurence matrix is required. | |
| preprocessed_reviews: A list of all the preprocessed reviews for which the co-occurence matrix is required. | |
| window_size: Suitable window size for which the co-occurence matrix is required. | |
| Returns: | |
| cooc: The calculated co-occurence matrix. |