GT data mining

Sunday, September 25, 2016

A perpetuum mobile of data – the essence of the IT revolution

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The essence of the Information Technology revolution, the engine that propels it, is the reality in todays' information systems, of d...
Friday, September 23, 2016

Is Machine Learning chasing its own tail (of presumptions)?

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Machine Learning  (ML) as a method of learning is indeed a machine, i.e. it operates consistently, repeatedly and predictably, by a designe...
Thursday, September 22, 2016

The law of Large Numbers fails in big data

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The law of Large Numbers is often regarded as a sort of "law of nature" by which variables' averages always gravitate to fixe...
Sunday, September 27, 2015

GT data mining demonstration - finances

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Prediction of the daily US $ up/down change Edith Ohri, edith@fabhighq.com The goal In this demo the goal has been ...
Tuesday, September 15, 2015

Digging in financial data

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Using any data for in-depth conclusions Lessons from a   GT study * of 1,000 NYSE companies from year 2000, just before the dot-com bubbl...
Thursday, June 13, 2013

Some thoughts on big data challenges

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Here is a list of challenges from my personal encounters with the subject: How to make use of unsupervised data?  Untangling mixed phen...
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Wednesday, June 5, 2013

First introduction

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Why GT, and why data mining at all? My quest for mining algorithm started a long while ago. I sort of grew up with that field.  It intrig...
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About Me

Edith Ohri
Through many works and researches I've developed the GT-data-mining universal solution to analytics of unsupervised data, which later has been proven to fit big data and machine-learning requirements as well. GT is made for find & define new hypotheses at the LEARNING stage. About the new data-science concept - see at https://www.researchgate.net/project/Philosophy-of-Data-Science-review-for-big-data-analytics
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