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Q6 Solve Following Practical Problem Company Wants Develop Music Classification Genre Usin Q43791828

Q6. Solve the following practical problem.

A company wants to develop a music classification by genre usingneural networks.

Question 6 (4+4+5+5=18 marks marks) Solve the following practical problem. A company wants to develop a music classification by genre using neural networks. Large amount of music songs data set has been collected and the data set contains features from symbolic songs (MP3, in this case), which can be used to classify the recordings by genre. Each cxample is classified as classic, rock, jazz or folk song. The attributes are duration of song, tempo, root mean square (RMS) amplitude, sampling frequency, sampling rate, dynamic range, tonality and number of digital errors. 1 Describe the neural network model for the classification task, and the possible split of the original data set into the training, validating and the testing data sets.. [4 marks) 2 How would you normalize the data? [4 marks] 3 If the performance of your model on the training set is good, but the test set performance is significantly worse, what is the most possible problem? Discuss a simple way that may improve your results. [5 marks] 4 Describe and explain two different measurements for the classification performance that you would use. Discuss any possible relationships between the two measure- ments. [5 marks] Show transcribed image text Question 6 (4+4+5+5=18 marks marks) Solve the following practical problem. A company wants to develop a music classification by genre using neural networks. Large amount of music songs data set has been collected and the data set contains features from symbolic songs (MP3, in this case), which can be used to classify the recordings by genre. Each cxample is classified as classic, rock, jazz or folk song. The attributes are duration of song, tempo, root mean square (RMS) amplitude, sampling frequency, sampling rate, dynamic range, tonality and number of digital errors. 1 Describe the neural network model for the classification task, and the possible split of the original data set into the training, validating and the testing data sets.. [4 marks)
2 How would you normalize the data? [4 marks] 3 If the performance of your model on the training set is good, but the test set performance is significantly worse, what is the most possible problem? Discuss a simple way that may improve your results. [5 marks] 4 Describe and explain two different measurements for the classification performance that you would use. Discuss any possible relationships between the two measure- ments. [5 marks]

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Answer to Q6. Solve the following practical problem. A company wants to develop a music classification by genre using neural netwo…