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SEIS 764 Artificial Intelligence© Dr. Chih Lai University of St. Thomas1Graduate Program in SoftwareSEIS 764: Artificial IntelligenceAssignment #5 (100 points)Due Date: October 6thThe dataset (CellDNA.csv) contains various measurements (i.e. size, center, etc) fromthousands of bacterium under microscope. The non-zero values in the last column arethe target responses that indicate the bacterium (rows) that are interesting enough forfurther study. The 0s in the last column indicate the bacterium (rows) are NOT interestingcandidates for further study. Convert this target dependent variable (last column) tobinary values of either 0s or 1s for your two-class classification.Write a program using either Python+Keras or MatLab to perform the two-classclassification analysis on this dataset using the neural network approach.Answer the following questions:1. Print the configurations (architecture) of all the layers in your neural network,AND put it in a WORD document.2. Print the confusion matrix of your classification result, and what is the accuracyof classification result? The accuracy can be obtained EITHER from trainingdata, test data, OR both. Please specify which dataset (i.e. training or testing) wasused to calculate the accuracy. Please include your results in the SAME WORDdocument.3. Print the precision, recall, F-score for EACH class. Also, create a ROC curvefor EACH class. Again, please include your results the SAME WORD document.4. Save your code as “a5.py”, “a5.ipynb”, or “a5.m”.Submission Guideline:1. Please include the WORD document your created in answering the abovequestions. Please include your name on the top of your WORD document.2. Please print your program (matlab or python) as PDF and include the PDF inyour submission.3. Please also include your program in the formats like .mat/.mlx/.py/.inpyb in yoursubmission.4. Prepare EVERYTHING mentioned in the submission guideline and submit themon Canvas no later than the due date. Please do NOT zip your files.
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