Summarize the major goal of your paper, the techniques used in the paper and the key results.

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

3. Final Report

Your report needs to have the following sections:

• Abstract: Summarize the major goal of your paper, the techniques used in the paper and the key results. (up to 300 words).

● This report determines the suitability of different confusion matrices, allowing us to visualize the performance of an algorithm and model for data regarding wine quality using python. These models include K-nearest neighbor (KNN), Support Vector Machines (SVM) and Random Forest (Decision Tree). Each model has different results that show the best model for wine quality predictions. Adjusting the attributes to get better results and understanding of what attributes are most important in the data.

 

 

• Introduction: Discuss the following items in the introduction:

o The background of the project and specify your problem.

● Wine has been tested by users of varying attributes. These users then give a number score to represent the quality of each wine. The data we were given includes different attributes along with the score. These included fixed acidity, citric acid, residual sugar, chlorides etc. These attributes are to be used to figure out what is most important when determining the quality of wine. 

o The importance or practical value of the problem

● In many situations there are attributes that contribute to the quality of a product. This problem at hand can be an example on how to determine the best attributes of any consumer product, given similar data. If given the same attributes of any wine we could use the best performing model to make a data based prediction on whether the wine would be considered high or low quality. 

 

• Methodology: Discuss the methodology you use.

● Determine the models that best forecast wine quality, then re-testing by removing attributes to see which attributes the data are most reliant on. 

Attachments:

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