Artificial intelligence algorithms performance analysis

Aamir khanaamirkhan.iba@gmail.com

IBA karachi, Pakistan

Data to be analyzed

Task:

• Use KNIME to perform classification on the given dataset. The dataset has been taken from UCI Mahine Learning repository and uses US census data to predict whether the income of a person exceeds $50K/yr. The details of the dataset can be found at

• http://archive.ics.uci.edu/ml/datasets/Adult• You have to experiment with different classification approaches

discussed in the course (i.e. Decision tree, Naive Bayes', Neural Networks) using different set of attributes. You may first need to do some data pre-processing to clean your data first.

• You are required to submit a report describing different experiments that you conducted (along with the screenshots of weka/ knime wherever appropriate) and their results.

Baive Bayes Workflow

String Manipulation for all three Due to error in data

Naïve Bayes Learner

Normalizer

Confusion Matrix and Accuracy of Naïve Bayes

Decision Tree Workflow

Decision tree learner

Confusion matrix and accuracy for Decision tree

ANN workflow

Column filter for ANN

Confusion matrix and Accuracy for ANN

Conclusion

• Results of our workflow shows that the given data has accuracy of 76.5% in ANN, 76.4 in Naïve Bayes and 83.2 in Decision tree on the basis of our configurations.

• Hence Decision tree gives best result on the provided data.