soil_fertility.py

# -*- coding: utf-8 -*-
"""Soil_Fertility.ipynb

Automatically generated by Colaboratory.

Original file is located at
    https://colab.research.google.com/drive/1e0L-RbqU98Ibi-dZuUuYd7KsgNgqsdDa
"""

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import tensorflow as tf

from sklearn.ensemble import RandomForestClassifier

df = pd.read_csv('/content/data (1).csv')

df.head()

from sklearn.model_selection import train_test_split

X = df.drop('Output',axis=1)
y = df['Output']

sns.pairplot(data=df,hue="Output")

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

rfc = RandomForestClassifier()

rfc.fit(X_train,y_train)

pred = rfc.predict(X_test)

from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay

cm = confusion_matrix(y_test, pred, labels=rfc.classes_)

disp = ConfusionMatrixDisplay(confusion_matrix=cm,
           display_labels=rfc.classes_)
disp.plot()
plt.show()

import pickle
pickle.dump(rfc,open('soil_fertility.pkl','wb'))