PROJECT
Title:
Construct baseline model for training and evaluating models using ML Tools.
Tools, Equipment and Materials:
1 Windows PC with Python editor, Python compiler, MSOffice installed, Web Browser.
Instructions:
You have to construct and test a ML (Machine Learning) model.
1 Browse to kaggle.com website to search for ‘binary categorical data’ where the target is a binary value.
2 Choose and download one of the listed datasets from the search results to predict the binary target.
3 Write a script to cleanse the downloaded datasets for the following from at least one of the columns:
a. Invalid data
b. Null values
c. Unknown values
4 Choose and convert one of the categorical column data to numeric values.
5 Create datasets from csv files using the required features and target.
6 Choose between supervised and unsupervised method for machine learning for the downloaded dataset.
7 Choose an appropriate machine learning algorithm to predict the binary target.
8 Build the model using the dataset and specify the appropriate parameters for the algorithm chosen in Step 7.
9 Select training data and test data from the dataset.
10 Train the machine learning model using the selected algorithm and dataset.
11 Use the test data selected in Step 9 to evaluate the model.
12 Demonstrate the results using the following parameters.
a. Accuracy of prediction
b. False Positives
c. False Negatives
d. True Positives
e. True Negatives
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