Data Science for Business

Profiling (also known as behavior description) attempts to characterize the typical behavior of an individual, group, or population. An example profiling question would be: “What is the typical cell phone usage of this customer segment?”

Co-occurrence grouping (also known as frequent itemset mining, association rule discovery, and market-basket analysis) attempts to find associations between entities based on transactions involving them

Clustering attempts to group individuals in a population together by their similarity

Similarity matching attempts to identify similar individuals based on data known about them

classification predicts whether something will happen, whereas regression predicts how much something will happen.

Regression is related to classification, but the two are different.

Regression (“value estimation”) attempts to estimate or predict

Classification and class probability estimation attempt to predict

A critical skill in data science is the ability to decompose a data-analytics problem into pieces

Deduction starts with general rules and specific facts, and creates other specific facts from them.