Bayesian Logistic Regression by Stan - Qiita

import numpy as np import matplotlib.pyplot as plt %matplotlib inline import seaborn as sns from sklearn.datasets import load_breast_cancer from sklearn.model_selection import train_test_split from sklearn.linear_model import LogisticRegression import pystan cancer = load_breast_cancer() indices = np.random.choice(len(cancer.data), 100, replace=False) data = cancer.data[indices, :5] target = cance