smadwer / adult-classification

Binary classification on adult dataset using logistic regression

Binary Classification on Adult Dataset using Logistic Regression with Plotting of Confusion Matrix

This code implements a binary classification model using logistic regression to predict whether a person's salary is greater than $50K or not based on various demographic and socio-economic factors. The confusion matrix is also plotted to evaluate the model's performance.

Libraries Used

• Pandas
• Scikit-learn
• Matplotlib

Dataset

The adult dataset is used for training and testing the model. The dataset contains information about 32,561 individuals, and the target variable is "salary".

Data Preprocessing

Irrelevant columns "education" and "native_country" are dropped. The target variable "salary" is encoded using LabelEncoder. Categorical features are encoded using one-hot encoding.

Model Building and Evaluation

• The dataset is split into training and testing sets.
• A logistic regression model is built and trained on the training set.
• The model's performance is evaluated on the testing set using accuracy score and confusion matrix.
• The confusion matrix is plotted using matplotlib.

Running the Code

Ensure that the required libraries are installed. Download the adult dataset as "adult.csv" and place it in the same directory as the code. Run the code.

Output

• The accuracy score of the model on the testing set is printed.
• The confusion matrix is plotted and displayed.