Learn practical skills, build real-world projects, and advance your career
Created 4 years ago
Finding best model and hyper parameter tunning using GridSearchCV
For iris flower dataset in sklearn library, we are going to find out best model and best hyper parameters using GridSearchCV
Load iris flower dataset
import numpy as np
from sklearn import svm, datasets
iris = datasets.load_iris()import pandas as pd
df = pd.DataFrame(iris.data,columns=iris.feature_names)
df['flower'] = iris.target
df['flower'] = df['flower'].apply(lambda x: iris.target_names[x])
df.head()