Question
1) Select the intention of the following machine learning algorithms: from sklearn.neighbors import KNeighborsClassifier classifier = KNeighborsClassifier(n_neighbors = 5, metric = 'minkowski', p = 2)
1) Select the intention of the following machine learning algorithms:
from sklearn.neighbors import KNeighborsClassifier
classifier = KNeighborsClassifier(n_neighbors = 5, metric = 'minkowski', p = 2)
classifier.fit(X_train, y_train) kmeans = KMeans(n_clusters = 5, init = 'k-means++', random_state = 42)
y_kmeans = kmeans.fit_predict(X)
Group of answer choices
a. overfit the data for classification and underfit the data for the clustering
b. Look for 5 closest neighbors and form 5 clusters
c. Only form 5 clusters
d. underfit the data for classification and overfit the data for the clustering
2) The cost function that is used in logistic regression is:
Group of answer choices
a. Mean Squared Error
b. Both of these
c. None of these
d. Maximum Likelihood
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