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High on Science | Science, algorithms & analysis.

Science, algorithms & analysis. (by William High)

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High on Science | Science, algorithms & analysis. | highonscience.wordpress.com Reviews
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Science, algorithms & analysis. (by William High)
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High on Science | Science, algorithms & analysis. | highonscience.wordpress.com Reviews

https://highonscience.wordpress.com

Science, algorithms & analysis. (by William High)

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Fast and lean ad hoc binary classifier evaluation | High on Science

https://highonscience.wordpress.com/2015/03/08/fast-and-lean-ad-hoc-binary-classifier-evaluation

Science, algorithms and analysis. Skip to primary content. Fast and lean ad hoc binary classifier evaluation. March 8, 2015. In this post I’m going to see if I can beat. Which is a C utility I’ve used that computes precision, recall, AUC, etc. I’ll be exploring streaming computation of some useful metrics:. Single-pass precision, recall, accuracy, lift and F1-score. Single-pass (plus a little) AUC. Data, procedure and result. I grabbed the biggest data set in Chih-Jen Lin. 19,264,097 training entities.

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Guaranteeing k samples in streaming sampling without replacement | High on Science

https://highonscience.wordpress.com/2015/04/15/guaranteeing-k-samples-in-streaming-sampling-without-replacement

Science, algorithms and analysis. Skip to primary content. Guaranteeing k samples in streaming sampling without replacement. April 15, 2015. When doing streaming sampling without replacement of a finite data set of known size. Data = LOAD 'data' AS (f1:int,f2:int,f3:int); X = SAMPLE data p;. Between 0 and 1. If you need at least. The table below helps in choosing. It reads like this: setting. To the specified value guarantees you’ll get at least. Of the time for any. Larger than 20 or so; for smaller.

3

Faking Filters in Linear Modeling: Proof of Concept | High on Science

https://highonscience.wordpress.com/2015/03/07/faking-filters-in-linear-modeling-proof-of-concept

Science, algorithms and analysis. Skip to primary content. Faking Filters in Linear Modeling: Proof of Concept. March 7, 2015. Linear models are extremely fast to train and score, but don’t handle filter logic natively when segmenting populations. To segment N populations you might train N linear models, which gets operationally messy when N is large. Hint: adding a simple binary feature indicating segment membership is not enough.). What I’m about to do, and results. I’m going to mock data from tw...

4

Parallel cardinality on your laptop | High on Science

https://highonscience.wordpress.com/2015/03/15/parallel-cardinality-on-your-laptop

Science, algorithms and analysis. Skip to primary content. Parallel cardinality on your laptop. March 15, 2015. This post is about showing your laptop who’s boss. It contains:. A cool set union command line snippet. A cool set intersection command line snippet. 3x speedups on everyday Unix commands useful to data scientists. A map-reduce command line paradigm that’s one better than the usual. Cat data.in map sort reduce data.out. A standard grep takes me 1m 39s. Grep 15577606 kddb wc -l. Features in the ...

5

William High | High on Science

https://highonscience.wordpress.com/author/fwhigh

Science, algorithms and analysis. Skip to primary content. Skip to secondary content. Author Archives: William High. Hi, I'm William. I'm a physicist turned data scientist. Auto prepend 4 spaces for Markdown code blocks. October 29, 2015. It becomes very cumbersome very quickly if you write Markdown and want to copy large code blocks into the source. Here’s a shortcut to prepend 4 spaces in just a couple steps for Mac users. Step 1: Create an appify script. Step 2: Create a pb2md script. Step 3: Appify it.

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High on Science | Science, algorithms & analysis.

Science, algorithms and analysis. Skip to primary content. Skip to secondary content. Guaranteeing k samples in streaming sampling without replacement. April 15, 2015. When doing streaming sampling without replacement of a finite data set of known size. Data = LOAD 'data' AS (f1:int,f2:int,f3:int); X = SAMPLE data p;. Between 0 and 1. If you need at least. The table below helps in choosing. It reads like this: setting. To the specified value guarantees you’ll get at least. Of the time for any. I got to t...

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High on Science & Tech – H.O.S.T | News from the Science and Tech World

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