When updating weights for a perceptron model, in which case would the weight need to decrease?

Which task describes a clustering data mining task?

How do we determine that a given data point is an outlier?

What is a disadvantage of utilizing decision tree models?

How do we determine that a given data point is a noise?

Figure 6: Dataset for Pet Type Instance Age Home Value ($Millions) Pet 1 28 3.6M Cat 2 33 4.1M Cat 3 38 3.7M Cat 4 48 3.9M Cat 5 48 3.5M Dog 6 58 3.7M Dog 7 63 3.1M Dog 8 68 3.6M Dog   Review the table labeled Figure 6: Dataset for Pet Type. If you train a Support Vector Machine (SVM) on the dataset to predict pet type, the result will include how many support vectors?

Compute the simple matching and Jaccard coefficient between X and Y: X = (0, 1, 0, 1) Y = (0, 1, 1, 1)

Figure 7: Artificial Neural Network Dataset Instance 1 2 3 4 5 6 7 8 9 Actual Class 1 1 -1 -1 1 -1 1 -1 1 Predicted Class -1 1 1 -1 1 1 -1 -1 -1   Review the table labeled Figure 7: Artificial Neural Network Dataset. A forward pass of an Artificial Neural Network finished and the data are classified in the table. What is the total sum of the squared errors?

When updating weights for a perceptron model, in which case would the weight need to increase?

Figure 2: Training Dataset for Pet Type Employed Age Debt College Degree Pet Yes 26 No Yes Cat Yes 45 Yes No Dog No 22 Yes Yes Dog No 50 No Yes Cat Yes 24 No Yes Cat No 33 Yes Yes Dog Yes 62 No No Cat Yes 39 No Yes Dog No 25 No Yes Dog   Review the table labeled Figure 2: Training Dataset for Pet Type. Assume we want to use a decision tree to predict a person’s pet type. Using misclassification error as the measure of node impurity, which attribute provides the best split?