From a binary class pespective
1+1=3
As simple as Logistic Regression
Validation model
When to split
Preprocessing
import numpy as np
import seaborn as sns;
import matplotlib.pyplot as plt; plt.style.use('ggplot')
N = int(10e6)
log_normal = np.random.lognormal(size=N)
var_log, mean_log = log_normal.var(), log_normal.mean()
var_log, mean_log
(4.658509594268878, 1.6486913090041344)
dist = sns.distplot(log_normal)
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log_normal_sample = np.random.choice(log_normal, size=int(0.3*N))
var_log_sample, mean_log_sample = log_normal_sample.var(), log_normal_sample.mean()
var_log_sample, mean_log_sample
(4.617970633233202, 1.6470042949353507)
dist_sample = sns.distplot(log_normal_sample)
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