Causal Machine Learning (MEAP V03)
English | 2022 | ISBN: 9781633439917 | 187 pages | PDF,EPUB | 7.02 MB
How do you know what might have happened, had you done things differently? Causal machine learning gives you the insight you need to make predictions and control outcomes based on causal relationships instead of pure correlation, so you can make precise and timely interventions.

Constructing Science
by Deena Skolnick Weisberg;David M. Sobel;
English | 2022 | ISBN: 0262044684 | 387 pages | True PDF EPUB | 27.58 MB

Wang Y Artificial Intelligence and Causal Inference 2022 | 22.31 MB
English | 395 Pages

Title: Artificial Intelligence and Causal Inference
Author: Momiao Xiong
Year: 2009

De Villa A Causal Inference for Data Science (MEAP v 4) 2022 | 9.44 MB
N/A | 163 Pages

Title: Causal Inference for Data Science MEAP V04
Author: Aleix de Villa Robert
Year: 2016

Johannes Dellert, "Information-theoretic causal inference of lexical flow"
English | ISBN: 3961101442 | 2019 | 384 pages | PDF | 3 MB
This volume seeks to infer large phylogenetic networks from phonetically encoded lexical data and contribute in this way to the historical study of language varieties. The technical step that enables progress in this case is the use of causal inference algorithms. Sample sets of words from language varieties are preprocessed into automatically inferred cognate sets, and then modeled as information-theoretic variables based on an intuitive measure of cognate overlap. Causal inference is then applied to these variables in order to determine the existence and direction of influence among the varieties. The directed arcs in the resulting graph structures can be interpreted as reflecting the existence and directionality of lexical flow, a unified model which subsumes inheritance and borrowing as the two main ways of transmission that shape the basic lexicon of languages. A flow-based separation criterion and domain-specific directionality detection criteria are developed to make existing causal inference algorithms more robust against imperfect cognacy data, giving rise to two new algorithms. The Phylogenetic Lexical Flow Inference (PLFI) algorithm requires lexical features of proto-languages to be reconstructed in advance, but yields fully general phylogenetic networks, whereas the more complex Contact Lexical Flow Inference (CLFI) algorithm treats proto-languages as hidden common causes, and only returns hypotheses of historical contact situations between attested languages. The algorithms are evaluated both against a large lexical database of Northern Eurasia spanning many language families, and against simulated data generated by a new model of language contact that builds on the opening and closing of directional contact channels as primary evolutionary events. The algorithms are found to infer the existence of contacts very reliably, whereas the inference of directionality remains difficult. This currently limits the new algorithms to a role as exploratory tools fo

Barbrook P Systems Mapping causal models of systems 2022 | 4.1 MB
N/A | 197 Pages

Title: Systems Mapping
Author: N/A
Year: N/A

Linkedin Learning - Machine Learning and AI Foundations Causal Inference and Modeling-XQZT
English | Tutorial | Size: 469.51 MB

Self-Determination and Causal Agency Theory: Integrating Research into Practice
English | 2022 | ISBN: 303104259X | 278 Pages | PDF EPUB (True) | 3 MB
This book introduces Casual Agency Theory as a framework for defining self-determination and describing its development and essential characteristics. It synthesizes the research on promoting and enhancing self-determination and explores implications for practice in a disability context across the life course. The book also highlights future directions for theory, research, and practice in areas of positive psychology and disability.

English | 2022 | ISBN: 1119704472 | 167 pages | True EPUB , PDF | 3.48 MB
Agent-based Models and Causal Inference Agent-based Models and Causal Inference

What Is Causal Inference | 1.49 MB
English | 43 Pages

Title: What Is Causal Inference?
Author: Hugo Bowne-Anderson, Mike Loukides
Year: 2019