eomlocal

from konlpy.tag import Kkma
from konlpy.utils import pprint

eomlocal

from collections import Counter
import random

def p_topic_given_document(topic, d, alpha=0.1):
    return ((document_topic_counts[d][topic] + alpha) /
            (document_lengths[d] + K * alpha))

def p_word_given_topic(word, topic, beta=0.1):
    return ((topic_word_counts[topic][word] + beta) /
            (topic_counts[topic] + V * beta))

eomlocal

import tensorflow as tf
import matplotlib.pyplot as plt

import math
import numpy as np

from sklearn.datasets import load_iris

data=load_iris()