Python Scikit-learn: Get the accuracy of the Logistic Regression
Python Machine learning Logistic Regression: Exercise-3 with Solution
In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables (or 'predictors').
Write a Python program to get the accuracy of the Logistic Regression.
import pandas as pd from sklearn.model_selection import train_test_split from sklearn import metrics from sklearn.linear_model import LogisticRegression iris = pd.read_csv("iris.csv") #Drop id column iris = iris.drop('Id',axis=1) X = iris.iloc[:, :-1].values y = iris.iloc[:, 4].values #Split arrays or matrices into train and test subsets X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20) model = LogisticRegression(random_state=0, solver='lbfgs',multi_class='multinomial').fit(X, y) model.fit(X_train,y_train) prediction=model.predict(X_test) print('The accuracy of the Logistic Regression is', metrics.accuracy_score(prediction,y_test))
The accuracy of the Logistic Regression is 0.9333333333333333
Python Code Editor:
Have another way to solve this solution? Contribute your code (and comments) through Disqus.
Previous: Write a Python program to create a scatter plot using sepal length and petal_width to separate the Species classes.
Next: Write a Python program to create a Bar plot to get the frequency of the three species of the Iris data.
What is the difficulty level of this exercise?
- New Content published on w3resource:
- Scala Programming Exercises, Practice, Solution
- Python Itertools exercises
- Python Numpy exercises
- Python GeoPy Package exercises
- Python Pandas exercises
- Python nltk exercises
- Python BeautifulSoup exercises
- Form Template
- Composer - PHP Package Manager
- PHPUnit - PHP Testing
- Laravel - PHP Framework