APPLICATION OF SUPERVISED LEARNING
MACHINE LEARNINGHARD QUESTIONS
|
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
|
|
|
Recognizing similarities
|
|
|
predicting
|
|
|
creatind patterns
|
|
|
all the above
|
Detailed explanation-1: -The predictions are most approximate with Linear Regression Algorithm.
Detailed explanation-2: -Long short-term memory (LSTM): Many experts currently consider LSTM as the most promising algorithm for stock prediction.
Detailed explanation-3: -With Machine Learning (ML) technology a price prediction problem is formulated as a regression analysis which is a statistical technique used to estimate the relationship between a dependent/target variable and single or multiple independent (interdependent) variables. In regression, the target variable is numeric.
Detailed explanation-4: -Thus, we introduce three different methods to select core influence factors of crude oil price, which are elastic-net regularized generalized linear Models (GlMNET), spike-slab lasso method (SSL) and Bayesian model averaging (BMA).