Machine Learning: An Applied Econometric Approach
Sendhil Mullainathan,Jann Spiess +1 more
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TLDR
This work presents a way of thinking about machine learning that gives it its own place in the econometric toolbox, and aims to make them conceptually easier to use by providing a crisper understanding of how these algorithms work, where they excel, and where they can stumble.Abstract:
Machines are increasingly doing “intelligent” things. Face recognition algorithms use a large dataset of photos labeled as having a face or not to estimate a function that predicts the pre...read more
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The Challenge of Big Data and Data Science
TL;DR: Burgeoning data and innovative methods facilitate answering previously hard-to-tackle questions about society by offering new ways to form concepts from data, to do descriptive inference, to make causal inferences, and to generate predictions.
Journal ArticleDOI
Synthesis, characterization and machine learning based performance prediction of straw activated carbon
TL;DR: In this paper, three kinds of straw, wheat straw, corn straw and sorghum straw, were used as the raw materials for the preparation of activated carbon co-activated by hydrothermal carbonization and pyrolysis.
Journal ArticleDOI
Data science for entrepreneurship research: studying demand dynamics for entrepreneurial skills in the Netherlands
Jens Prüfer,Patricia Prüfer +1 more
TL;DR: The most prominent data science methods suitable for entrepreneurship research are described and links to literature and Internet resources for self-starters are provided and it is concluded that further studies of entrepreneurial skills in the general population—outside the domain of entrepreneurs—is a rewarding subject for future research.
Journal ArticleDOI
No perfect storm for crop yield failure in Germany
Heidi Webber,Gunnar Lischeid,Michael Sommer,Robert Finger,Claas Nendel,Thomas Gaiser,Frank Ewert +6 more
ReportDOI
Peer Effects in Product Adoption
TL;DR: In this article, the authors studied the effect of peer effects in the market for new cell phones and found that a new phone purchase by a friend has a substantial positive and long-term effect on an individual's own demand for phones of the same brand, most of which is concentrated on the particular model purchased by the friend.
References
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction
TL;DR: The Elements of Statistical Learning: Data Mining, Inference, and Prediction as discussed by the authors is a popular book for data mining and machine learning, focusing on data mining, inference, and prediction.
Journal ArticleDOI
Problems with Instrumental Variables Estimation when the Correlation between the Instruments and the Endogenous Explanatory Variable is Weak
TL;DR: In this article, the use of instruments that explain little of the variation in the endogenous explanatory variables can lead to large inconsistencies in the IV estimates even if only a weak relationship exists between the instruments and the error in the structural equation.
Journal Article
On Model Selection Consistency of Lasso
Peng Zhao,Bin Yu +1 more
TL;DR: It is proved that a single condition, which is called the Irrepresentable Condition, is almost necessary and sufficient for Lasso to select the true model both in the classical fixed p setting and in the large p setting as the sample size n gets large.
Journal ArticleDOI
Clinical versus actuarial judgment
TL;DR: Research comparing these two approaches to decision-making shows the actuarial method to be superior, factors underlying the greater accuracy of actuarial methods, sources of resistance to the scientific findings, and the benefits of increased reliance on actuarial approaches are discussed.
Book
A Distribution-Free Theory of Nonparametric Regression
TL;DR: How to Construct Nonparametric Regression Estimates * Lower Bounds * Partitioning Estimates * Kernel Estimates * k-NN Estimates * Splitting the Sample * Cross Validation * Uniform Laws of Large Numbers