FineReport

JULY 16, 2021

In addition, it can extract useful data from different business systems of an enterprise for storing, analyzing, and managing internal data. When we talk about business intelligence system, it normally includes the following components: data warehouse BI software Users with appropriate analytical. Data Mining.

Business Intelligence 98

Business Intelligence Informatics Data Warehouse Data mining 98

Domino Data Lab

MAY 20, 2021

We present the inner workings of the SMOTE algorithm and show a simple “from scratch” implementation of SMOTE. 2002) do not present a rigorous mathematical treatment for this modification, and the suggested median correction appears to be purely empirical-driven. Data mining for direct marketing: Problems and solutions.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

Recently, we presented some basic insights from our effort to measure and predict long-term effects at KDD 2015 [1]. References [1] Henning Hohnhold, Deirdre O'Brien, Diane Tang, Focus on the Long-Term: It's better for Users and Business , Proceedings 21st Conference on Knowledge Discovery and Data Mining, 2015. [2]

Modeling 61

Modeling Experimentation Knowledge Discovery Testing 61

Domino Data Lab

AUGUST 1, 2021

Toy example to present intuition for LIME from Ribeiro (2016). Conference on Knowledge Discovery and Data Mining, pp. The black-box model’s complex decision function (unknown to LIME) is represented by the blue/pink background, which cannot be approximated well by a linear model. Guestrin, C., Bahdanau, D.,

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

The Unofficial Google Data Science Blog

JULY 22, 2020

Just as in ramp-up, making inferences while ignoring the complexity of time-based confounders that are present can lead to biased estimates. This post will discuss how to use data from a MAB to get unbiased estimates. Thus we have conditional ignorability no matter how many time-based confounders are present. 2015): 37-45. [3]

Experimentation 95

Experimentation Statistics Testing Strategy 95

The Unofficial Google Data Science Blog

JANUARY 14, 2016

by AMIR NAJMI Running live experiments on large-scale online services (LSOS) is an important aspect of data science. Indeed, understanding and facilitating user choices through improvements in the service offering is much of what LSOS data science teams do.

Experimentation 41

Experimentation Statistics Metrics Measurement 41