Figure 5: Training Dataset for Car Type Instance Work Years College Years Car Type 1 4 5.5 Hybrid 2 5 3 Sports 3 4 3.5 Luxury 4 3.5 4.5 Family 5 5 4 Hybrid 6 1 4 Sports 7 4 6 Luxury 8 6 4 Family 9 3 3 Hybrid 10 4.5 4 Sports 11 3 2 Luxury 12 4 2 Family Review the table labeled Figure 5: Training Dataset for Car Type. You decide to use the K-Nearest Neighbors (KNN) model on the dataset to predict car type. Your friend worked for 4 years and attended college for 4 years. If K is set to 7 and the model uses Euclidean distance, which car type will be predicted for your friend?

What is a disadvantage of using the K-Nearest Neighbors (KNN) model for classification?

Three classification models were trained on a dataset of previous bank transactions with the goal of detecting fraudulent transactions. The first model (M1), which is complex, has a training error of 0.0034. The second model (M2), which is simpler, has a training error of 0.0047. The third model (M3), which is the simplest, has a training error of 0.1251. Which model would be the best one to use for classifying future transactions?

You trained a model to predict stock market prices. Your model performs well on your dataset, but performs poorly on a different dataset. How can you improve your model?

You want to train a model for detecting stones that contain gold. A mining company has a dataset of 5 million stone images, of which only 500 contain gold. What is the best measure to evaluate your model if you designate stone images with gold as the positive class?

You have a dataset of 5,000 audio files, and you want to train a model to detect music files within the dataset. How would you validate the performance of your classifier?

You are given a dataset of cars and asked to train a decision tree to classify the cars into two classes: Luxury and Sports. If a leaf node contains 100 cars, which case would provide better performance? (L represents the Luxury class, and S represents the Sports class.)

What is an underlying assumption of Naive Bayes Classification?

You want to train a model for detecting bald eagles. National Geography provides you a dataset of 1 million bird images, of which only 200 are bald eagles. What is the best measure to evaluate your model if you designate bald eagles as the positive class?

Compute the cosine similarity and correlation coefficient between feature vectors X and Y: X = (4, 2, 3, 3) Y = (1, 3, 5, 7)