Arrange the steps executed in the k-nearest neighbor classification algorithm. Group of answer choices Step 1 Scale measures to rescale the feature to have a zero mean and unit variance. Step 2 Compute distance between two points (e.g., Euclidean distance). Step 3 Determine the class from the k-nearest neighbors by taking the majority vote of class labels among the k-nearest neighbors. Step 4 Determine the class from the k-nearest neighbors by taking the majority vote of class labels among the k-nearest neighbors