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All Blog Posts Tagged 'accuracy' (4)

What is the most robust binary-classification performance metric?

Accuracy, F1, or TPR (a.k.a recall or sensitivity) are well-known and widely used metrics for evaluating and comparing the performance of machine learning based classification.

But, are we sure we evaluate classifiers' performance correctly? Are they or others such as BACC (Balanced Accuracy),…

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Added by Gürol Canbek on August 24, 2021 at 9:00pm — No Comments

Best practices of Data Cleansing

Data Accuracy:

Data accuracy is the biggest challenge for many businesses, having accurate data is useful in all its stages to use. Data results in inaccuracies when it is created, collected or during the clean-up, or when being stored. The inconsistencies from any of the sources make the data useless or less…

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Added by Indhu on March 12, 2021 at 12:22am — No Comments

The Value of Accuracy in Predictive Analytics

This article was first posted in 2014 but the message bears repeating.  There is a lot being written about tools simple enough for the citizen data scientist to operate.  The unstated constraint is that if you don't have significant experience in data science then these will always be "good enough" models.  The problem is that 'good enough' models under achieve both revenue and profit.  Very small increases in model fitness can translate into much larger increases in campaign ROI.  Business…

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Added by William Vorhies on October 8, 2014 at 8:00am — 4 Comments

Hazards of Institutional Data

A prominent discrimination case in Canada involves a firefighter named Tawney Meiorin.  Meiorin had successfully performed her duties as a firefighter for many years.  She lost her job after the introduction of mandatory testing to determine her fitness for the position.  The testing measured aerobic capacity, and it was developed in a manner that many would regard as scientific; that is to say, it used a highly quantitative and analytic approach.  However,…

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Added by Don Philip Faithful on November 23, 2013 at 4:43am — 1 Comment

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