FAQ on Machine Learning

Statistical learning techniques allow learning a function or predictor from a set of observed data that can make predictions about unseen or future data. These techniques provide guarantees on the performance of the learned predictor on the future unseen data based on a statistical assumption on the data generating process. Batch statistical learning refers to … Read more

The areas in robotics and information processing where sequential prediction problem arises are Imitation Learning Structured prediction Model based reinforcement learning In robotics and information processing, sequential prediction problems commonly arise in several areas, including: Robotics Control: Sequential prediction is crucial for tasks such as robot motion planning and control. Predicting the next state of … Read more

The different methods to solve Sequential Supervised Learning problems are Sliding-window methods Recurrent sliding windows Hidden Markow models Maximum entropy Markow models Conditional random fields Graph transformer networks In sequential supervised learning, the data arrives in a sequential manner, and the model learns from this data incrementally, updating its parameters as new examples become available. … Read more

The important components of relational evaluation techniques are Data Acquisition Ground Truth Acquisition Cross Validation Technique Query Type Scoring Metric Significance Test Relational evaluation techniques in the context of machine learning typically involve assessing the performance of a model in relation to some ground truth or benchmark. The components of relational evaluation techniques typically include: … Read more

Support vector machines are supervised learning algorithms used for classification and regression analysis. Support Vector Machines (SVMs) are a supervised learning algorithm used for classification and regression tasks. The primary objective of SVM is to find a hyperplane in an N-dimensional space (where N is the number of features) that distinctly classifies the data points … Read more