Clustering is ___________ and is example of ____________learning

Related MCQs

• Supervised learning differs from unsupervised clustering in that supervised learning requires
• What is true about K-Mean Clustering? 1. K-means is extremely sensitive to cluster center initializations 2. Bad initialization can lead to Poor convergence speed 3. Bad initialization can lead to bad overall clustering
• Hierarchical clustering is slower than non-hierarchical clustering?
• Supervised learning and unsupervised clustering both require which is correct according to the statement.
• Supervised learning and unsupervised clustering both require at least one
• Machine learning techniques differ from statistical techniques in that machine learning methods
• Which of the following are correct statement(s) about stacking? 1. A machine learning model is trained on predictions of multiple machine learning models 2. A Logistic regression will definitely work better in the second stage as compared to other classification methods 3. First stage models are trained on full / partial feature space of training data
• True or False: Ensemble learning can only be applied to supervised learning methods.
• In machine learning, an algorithm (or learning algorithm) is said to be unstable if a small change in training data cause the large change in the learned classifiers. True or False: Bagging of unstable classifiers is a good idea
• Which of the following are correct statement(s) about stacking? A machine learning model is trained on predictions of multiple machine learning models A Logistic regression will definitely work better in the second stage as compared to other classification methods First stage models are trained on full / partial feature space of training data