ISYE 6501 Mid Term 1|2023 LATEST UPDATE|WITH 100% CORRECT ANSWERS|100% PASS

What is modeling? Describing a real life situation mathematically Model Mathematical approaches to solving analytics problems 1. Regression for ex. can be called the model of choice. 2. If more detail (descriptive and numerical), the use of, for ex. Regression, can be called the model. 3. The actual values and output along with 1 and 2 can be referred to as the model. Cross Cutting Concepts Preparing data, measuring the quality of a model's output, missing data, etc.. Classification The process of grouping things based on their similarities Ex. Classifying consumers by who is likely to pay back a loan and who is not Soft Classifier A soft classifier is used when it is not possible to completely separate two categories of data points via the classifying line. the soft classifier gives as good of a separation as possible rather than a hard classifier that separates perfectly. Classifier Rules Must define the best separator. Misclassifying a data point may be more detrimental than misclassifying another. the more costly one bad decision is, the more we want to move away from it. Its okay to push the classifier in one direction so that it is conservative if stakes are higher. Data Point Every Row, a single observation of information Attribute/Feature/Covariate/Predictor Piece of information, column of data Responses/Outcomes Special type of column known as being the answer for each data point Structured Data Can be easily described and stored Unstructured Data Usually in form of text, cannot be easily described or stored Quantitative Data Most numerical data, numbers have a meaning Non Quantitative Data Descriptive data, Categorical data, any data without numerical meaning ex. zip codes Categorical Data numerical data that does not have quantitative meaning