Switching data mining algorithms might feel like navigating through a maze. You're not just changing a few lines of code; you're potentially overhauling your entire data strategy. The process ...

Learn how to select a machine learning algorithm for data mining based on the problem, the data, the performance, and the trade-offs.

Data mining is more about process than it is about clever algorithms. When the process is not well understood, all the clever techniques and algorithms can get applied to the wrong data, in the ...

So if race is disproportionately (but not explicitly) represented in the data fed to a data-mining algorithm, the algorithm can infer race and use race indirectly to make an ultimate decision.

Recent advances in data mining and mathematical modelling have increasingly influenced the development of sophisticated algorithms across diverse application domains. By extracting hidden ...

With the rapid development of big data and artificial intelligence technologies, the scale and complexity of financial data continue to increase, and traditional analysis methods can no longer meet ...

Specialization: Data Mining Foundations and Practice Instructor: Dr. Qin (Christine) Lv, Associate Professor of Computer Science Prior knowledge needed: Familiarity of functionalities in Python, basic ...

Training an algorithm on data from Alaska and applying it to Nevada means it might have a lot of wrong assumptions.” But the payoff from a big find can be stupendous.