Main

related bits

0

processing priority

4

site type

3 (personal blog or private political site, e.g. Blogspot, Substack, also small blogs on own domains)

review version

11

html import

20 (imported)

Events

first seen date

2024-10-21 22:41:27

expired found date

-

created at

2024-10-21 22:41:27

updated at

2026-03-11 21:10:30

Domain name statistics

length

23

crc

51859

tld

2211

nm parts

0

nm random digits

0

nm rare letters

0

Connections

is subdomain of id

94374219 (alpha-analysis.com)

previous id

0

replaced with id

0

related id

-

dns primary id

0

dns alternative id

0

lifecycle status

0 (unclassified, or currently active)

Subdomains and pages

deleted subdomains

0

page imported products

0

page imported random

0

page imported parking

0

Error counters

count skipped due to recent timeouts on the same server IP

0

count content received but rejected due to 11-799

0

count dns errors

0

count cert errors

0

count timeouts

0

count http 429

0

count http 404

0

count http 403

0

count http 5xx

0

next operation date

-

Server

server bits

server ip

-

Mainpage statistics

mp import status

20

mp rejected date

-

mp saved date

-

mp size orig

149679

mp size raw text

39581

mp inner links count

34

mp inner links status

20 (imported)

Open Graph

title

Data Science, Machine Learning and Predictive Analytics

description

Blog about data science, machine learning, AI, predictive analytics and the R programming language. Silicon Valley, CA

image

site name

author

updated

2026-03-08 21:49:11

raw text

Data Science, Machine Learning and Predictive Analytics Data Science, Machine Learning and Predictive Analytics Silicon Valley, CA R: Improving Regression Speed with Rcpp and RcppArmadillo I am going to demonstrate how to improve speed in R when performing multiple linear regression. Below I compare three methods: The standard built in R function for regression is lm() . It is the slowest. A bare bones R implementation is lm.fit() which is substantially faster than lm() but still slow. The fastest method to perform multiple linear regression is to use Rcpp and RcppArmadillo which is the C++ Armadillo linear algebra library .   A 1253 x 26 design matrix (X) is built from the cars_19 dataset and a simulation is run to compare the three methods: The cars_19 dataset from previous posts: str(cars_19) 'data.frame': 1253 obs. of 12 variables: $ fuel_economy_combined: int 21 28 21 26 28 11 15 18 17 15 ... $ eng_disp : num 3.5 1.8 4 2 2 8 6.2 6.2 6...

Text analysis

redirect type

0 (-)

block type

0 (no issues)

detected language

1 (English)

category id

Zastosowania AI (149)

index version

1

spam phrases

0

Text statistics

text nonlatin

0

text cyrillic

0

text characters

25475

text words

6312

text unique words

857

text lines

834

text sentences

219

text paragraphs

94

text words per sentence

28

text matched phrases

0

text matched dictionaries

0

RSS

rss path

rss status

1 (priority 1 already searched, no matches found)

rss found date

-

rss size orig

0

rss items

0

rss spam phrases

0

rss detected language

0 (awaiting analysis)

inbefore feed id

-

inbefore status

0 (new)

Sitemap

sitemap status

34 (reserved: import paused pending content quality/relevance assessment after importing first 500 pages)

sitemap review version

2

sitemap urls count

17

sitemap urls adult

0

sitemap filtered products

0

sitemap filtered videos

0

sitemap found date

2024-10-21 22:41:27

sitemap process date

2024-10-21 22:41:29

sitemap first import date

-

sitemap last import date

2025-12-08 01:50:40