asteroza + correlation   15

[1412.3773] Distinguishing cause from effect using observational data: methods and benchmarks
The basic intuition behind the method demonstrated by Prof. Joris Mooij of the University of Amsterdam and his co-authors is surprisingly simple: if one event influences another, then the random noise in the causing event will be reflected in the affected event.
statistics  correlation  causation  additive  noise  observation  research  mathmatics  Delicious  mathematics 
january 2015 by asteroza

related tags

2.0  account  additive  aggregator  AI  ajax  alternative  amp  analysis  analytics  archive  assessment  audio  authentication  automation  behaviour  blog  blueteam  Canada  causation  chart  collection  collector  community  comparison  console  consumption  correlation  correlations  cryptomneme  data  defense  Delicious  demand  DFIR  directed  disney  engine  evaluattion  event  facial  FIDO  flushing  google  graph  hacking  history  hockey  humor  IDS  image  information  internal  intranet  IPS  iterative  labs  learning  link  linking  LMDB  log  logging  machine  management  mashup  matching  mathematics  mathmatics  media  memory  monitoring  NBA  netflix  network  Nmap  noise  observation  olympics  ondemand  opensource  orchestration  OSINT  passmemory  password  pentesting  picture  platform  prioritization  processing  profile  profiling  python  Q1  recognition  recon  recursive  reference  relationship  remediation  research  resource  risk  scanning  search  searchCrystal  security  SEIM  SEM  semantic  server  service  sharing  SIEM  SIM  SNS  social  software  sound  spraying  statistics  survey  sysadmin  technology  threat  toilet  tools  tracking  trend  user  utilities  utility  visual  visualization  vul  vulnerability  water  web  widgets  windows 

Copy this bookmark:



description:


tags: