ASSIGNMENT PROBLEM STATEMENT

There are three tasks, and each consists of different steps, and our assignment is to make accurate predictions using

different classifiers. Proper preprocessing should be done before building a model, and the model should make

accurate predictions. You should compare at least four classifiers to select the best one.

Classifiers

Decision Tree Classifier

Parameters tuned $-$ max$\_$depth $=4,$ min$\_$samples$\_$split $=276,$ criterion $=$ 'gini'

$,$ Support Vector Machine Classifier$($SVM$)$

Parameters tuned $-$ kernel $=$ 'linear'

Naive Bayes $-$ Bernoulli and Gaussian

Parameter tuned $-$ None

Random Forest Classifier

Parameter tuned using RandomizedSearchCV

Task $1$:

Dataset: you have two choices to select the data, either using the available dataset or data scraping $($Crawling$).$

A$.$ Describe the data $($shape of the data, no$.$ of features and samples$)$ and compute the basic statistics of given

data $($mean$,$ median, and std$).$

B$.$ Exploratory Data Analysis $($EDA$)$

Task $2$:

Data Preprocessing:

A$.$ Handling Missing Values by Basic Methods.

B$.$ Use the Normalization technique.

Task $3$:

Building Model:

A$.$ Select at least four classifiers to predict the class label.

B$.$ Divide data into $70\%$ for training and $30\%$ for testing.

C$.$ Calculate the accuracy of your model using accuracy and F$1\_$score measures.

D$.$ Plot Confusion Matrix For the classes with labels.

E$.$ Visualize the Results

Example of the Visualize the Results