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1. Data Loading and Exploration:
The scikit-learn library was used to import the Iris dataset to start the study.
Necessary investigative steps included:
Relationships Between Features:
We investigated the connections between features using correlation matrices and
heatmaps to show the correlations.
Box plots were used to identify outliers, and it was found that the dataset lacked
Check for Normalization:
After analyzing the feature distributions, it was determined that normalization was
not required because the feature scales were similar.
Missing Values Check:
Confirmed that the dataset had all the values.
2.1 Decision Tree Classifier:
A Decision Tree Classifier was implemented, and ideal scores were obtained for
accuracy, precision, and recall (1.0).
2.2 Random Forest Classifier:
Used a Random Forest Classifier and obtained identical 1.0 score …
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