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89 def logistic_regression(w, x): 90 """Logistic regression classifier model. 91 92 w: Weights w. (n_features,) NumPy array 93 x: Data point x_i. (n_features,) NumPy array 94 -> float in [0, 1] 95 """ 96 return scipy.special.expit(numpy.dot(x, w.T))
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101 def run_logistic_regression(df): 102 # Logistic regression 103 X = df['pageviews_cumsum'] 104 X = sm.add_constant(X) 105 y = df['is_conversion'] 106 logit = sm.Logit(y, X) 107 logistic_regression_results = logit.fit() 108 print(logistic_regression_results.summary()) 109 return logistic_regression_results