This repository contains code and resources for performing classification analysis on the Iris dataset using IBM SPSS Statistics software.
The Iris dataset is a famous dataset in the field of machine learning and statistics. It contains measurements of various iris flowers, categorized into three species: setosa, versicolor, and virginica. In this project, we utilize SPSS to analyze this dataset and build classification models to predict the species of iris flowers based on their measurements.
iris_data.csv
: CSV file containing the Iris dataset.iris_analysis_syntax.sps
: SPSS syntax file for data analysis.iris_classification_report.pdf
: Report documenting the classification analysis results.README.md
: This file providing an overview of the repository.
- Data Preparation: Ensure
iris_data.csv
is in the appropriate directory. - SPSS Analysis: Open
iris_analysis_syntax.sps
in SPSS and execute the syntax to perform analysis. - Review Results: Refer to
iris_classification_report.pdf
for detailed analysis results and insights.
Feel free to clone this repository and use the provided resources for your own analysis or experimentation.