According to S&P, funds raised by junior and intermediate miners nearly quadrupled to $1.61 billion in October, the highest ...

Data mining blends the best of both worlds. It uses algorithms to dig up hidden patterns and relationships in data that are ...

Long used in the financial services and insurance industries, predictive analytics is about using statistics, data mining, and game theory to analyze current and historical facts in order to make ...

Data mining has been defined as “the nontrivial extraction of implicit, previously unknown, and potentially useful information from data”. 1 In areas other than the life sciences and ...

Data mining software is used to sort large amounts of data and identify or mine relevant information. Applications use advanced search capabilities and statistical algorithms to identify patterns and ...

data mining is most successful when it's used with rigidly defined goals. The Cross-Industry Standard Process for Data Mining (CRISP-DM) is one of the leading approaches to data mining.

A practical approach to data mining with large volumes of complex data; prepare, cleanse and visualise data; supervised and unsupervised modelling; ensemble and bundling techniques; use of leading ...