Nursery-Admission-Prediction

Nursery Admission Prediction uses Machine Learning classification algorithms to categorize whether the candidate is priority, recommended or not recommended to be admitted.

Classification algorithms used are:

• Support Vector Machines
• Random Forest
• Logistic Regression
• XGBoost

The dataset is Nursery Data Set.
The accuracy of prediction is displayed for each algorithm.
Label Encoder and get_dummies() is used for converting categorical data into numeric data,
Extra Tree Classifier,SelectKBest and Chi-Square for Feature Selection

BEFORE RUNNING THE CODE

• Paste the address of the directory where your Nursery.csv file is saved
  Eg. dataset = pd.read_csv(r'C:\Projects\NurseryAdmissionPrediction\Nursery.csv').
• Install XGBoost via the command prompt.
  conda install -c anaconda py-xgboost(for Anaconda prompt)