Archive

Archive for the ‘Data Mining’ Category

Stats

Authors@Google: Nate Silver
http://www.youtube.com/watch?v=mYIgSq-ZWE0&feature=em-uploademail

Probablistic Programming & Bayesian Methods for Hackers
http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/

Advertisements

Big Data

Categories: Analytics, Data, Data Mining Tags:

Hadoop

Categories: Analytics, Data, Data Mining Tags:

Model Thinking Part 3 – Coarsera

Tipping Point

  • Can be direct cause which is something causes the tip — small action or event (small change in variable) has large impact on end state — this depends also on context
  • Can be contextual  (percolation model is example) which means something in context changes to permit tip – a slight change in the context (environment)can have a big impact on final state
  • Between and within class — system can go within the class from one state to another or the system can go between states across systems

Note:  4 types of systems: equilibrium , periodic, random, complex

Percolation Model – physics model – water percolating down into ground is example

use a checker board model with filled in squares to show tipping point (59.27%) at which a process goes from start to finish (end) used in information flow, forest fire prediction, innovation flow, social model (context changes if more connections are made)

Diffusion Model –  natural diffusion but no tipping point

W sub t (time) = W sub-t (time) (current state) + N * c(number * contact rate) * t (tau – transmission rate) * W sub-t (time) /N (people with disease  / number) * (W sub-t (time) – N / N)

SIS– S (for susceptible), I (for infectious) and S (for susceptible). epidemiology —  non-linear – diffusion model  but person can get cured than reinfected — has a tipping point because people can be cured — this can alos apply to information

W sub t (time) = W sub-t (time) (current state) + N * c(number * contact rate) * t (tau – transmission rate) * W sub-t (time) /N (people with disease  / number) * (W sub-t (time) – N / N) – a [# of people cured)W (sub t) — this can be simplified using standard algebra notation

Basic Reproduction Number is R sub 0 = ct/a then if R sub 0> 1 disease spreads , hence a tipping point

V = % vaccinated  so R sub0(1 – V) = r sub 0 he< or equal to V nce 1 – 1/R sub 0 = number to vaccinate — must get to the number to vaccinate percentage (R sub 0) to create the tipping point needed to protect those people not vacinnated.  If R sub 0 < or + 1, no spread of disease, but if / or > than 1, disease will spread

Economic Models

Real growth is growth – inflation

Linked Data Graph Orientated Frameworks

January 9, 2012 Comments off

Glossary of Semantic Technology Terms
http://www.mkbergman.com/1017/glossary-of-semantic-technology-terms/

The Rationale for Semantic Technologies
http://www.mkbergman.com/1015/the-rationale-for-semantic-technologies/

Ontologies as Conceptual Models
http://www.cambridgesemantics.com/blog/-/blogs/ontologies-as-conceptual-models?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+EnterpriseSemantics+%28Enterprise+Semantics+Blog%29

The Rationale for Semantic Technologies
http://www.mkbergman.com/1015/the-rationale-for-semantic-technologies/?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+AI3_AdaptiveInformation+%28AI3%3A%3A%3AAdaptive+Information%29

JSON-LD by Manu Sporny

https://www.youtube.com/watch?feature=player_embedded&v=vioCbTo3C-4#!

Semantic Web Intro by Manu Sporny
http://bit.ly/Kw6Asm

Linked Data Intro by Manu Sporny
http://www.youtube.com/watch?v=4x_xzT5eF5Q

Linked Data FAQ
http://structureddynamics.com/linked_data.html

Linked Data – Welcome to the Data Network (may behind a pay wall)
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6062547

Pregel
http://www.michaelnielsen.org/ddi/pregel/

Google Pregel Graph Processing
http://horicky.blogspot.com/2010/07/google-pregel-graph-processing.html

Pregel: a system for large-scale graph processing – “ABSTRACT”
http://delivery.acm.org/10.1145/1590000/1582723/p6-malewicz-2.pdf?ip=99.5.73.174&acc=ACTIVE%20SERVICE&CFID=61362319&CFTOKEN=25119961&__acm__=1326116961_4c5dbb95b82d3aaedcc9b134c8fd4318

Pregel a system for larescale graph processing slides

http://www.slideshare.net/shatteredNirvana/pregel-a-system-for-largescale-graph-processing

GoldenOrb
http://goldenorbos.org/

Signal/Collect
http://code.google.com/p/signal-collect/

Data Science

August 15, 2011 Comments off