Ejercicio clasificación#

Utilice la base de datos Classification.csv para crear un modelo que clasifique los datos con una accuracy de al menos un 90%.

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.read_csv("Classification.csv", sep = ";", decimal=",")
print(df.head())

          X1          X2  y
0 -16.374564  211.035503  1
1 -21.845987    6.262558  1
2  -7.987957   -8.449664  0
3  11.008814   82.381994  0
4   3.524531   35.596753  0

plt.scatter(df["X1"], df["X2"], c = df["y"])
plt.xlabel("X1")
plt.ylabel("X2");
../../../_images/output_4_06.png 
X = df[["X1", "X2"]]
print(X.head())

          X1          X2
0 -16.374564  211.035503
1 -21.845987    6.262558
2  -7.987957   -8.449664
3  11.008814   82.381994
4   3.524531   35.596753

X.shape

(10000, 2)

y = df["y"]
print(y.head())

0    1
1    1
2    0
3    0
4    0
Name: y, dtype: int64