随笔分类 - 数据挖掘
数据挖掘知识点及应用案例分享
摘要：Converting to NIMBLE from JAGS, OpenBUGS or WinBUGS NIMBLE is a hierarchical modeling package that uses nearly the same modeling language as the popul
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摘要：I was surprised by greta. I had assumed that the tensorflow and reticulate packages would eventually enable R developers to look beyond deep learning
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摘要：This weekend, I decided it was time: I was going to update my Python environment and get Keras and Tensorflow installed so I could start doing tutoria
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摘要：As with many aspects of the tidyverse, its non-standard evaluation (NSE) implementation is not something entirely new, but built on top of base R. Wha
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摘要：Unsupervised learning refers to data science approaches that involve learning without a prior knowledge about the classification of sample data. In Wi
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摘要：@drsimonj here to show you how to conduct ridge regression (linear regression with L2 regularization) in R using the glmnet package, and use simulatio
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摘要：Today, I want to show how I use Thomas Lin Pederson’s awesome ggraph package to plot decision trees from Random Forest models. I am very much a visual
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摘要：Reinforcement learning has gained considerable traction as it mines real experiences with the help of trial-and-error learning to model decision-makin
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摘要：factoextra is an R package making easy to extract and visualize the output of exploratory multivariate data analyses, including: Principal Component A
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摘要：Introduction Deep learning is a recent trend in machine learning that models highly non-linear representations of data. In the past years, deep learni
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摘要：@drsimonj here to show you how to use xgboost (extreme gradient boosting) models in pipelearner. Why a post on xgboost and pipelearner? xgboost is one
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摘要：There is a plethora of classification algorithms available to people who have a bit of coding experience and a set of data. A common machine learning
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摘要：Previously in this series: The beta distribution Empirical Bayes estimation Credible intervals The Bayesian approach to false discovery rates Bayesian
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摘要：This example shows how to construct and conduct inference on a state space model using particle filtering algorithms. nimblecurrently has versions of
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摘要：本文综合了Pablo的博客和Carlos E.Perez的博客，经作者授权，由InfoQ中文站社区编辑刘志勇编译整理并分享。 深度学习在机器学习领域中一直是核心话题，在过去几年和2016年也是如此。在本文中将阐述我们认为该领域中最有贡献（或最有潜力）的进展，以及组织和社区如何确保这些强大的技术对所有
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摘要：@drsimonj here to share a tidyverse method of grid search for optimizing a model’s hyperparameters. Grid Search For anyone who’s unfamiliar with the t
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摘要：When faced with classification tasks in the real world, it can be challenging to deal with an outcome where one class heavily outweighs the other (a.k
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摘要：If your regression model contains a categorical predictor variable, you commonly test the significance of its categories against a preselected referen
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摘要：原文在此：8 Trips to Combat Imbalanced Classes in You Machine Learning Dataset by Jason Brownlee 当你遇到非均衡数据集的时候，即便是你得到准确率为90%的分类模型，只要你仔细研读你会发现，分类中基本都是某一类。 C
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摘要：In the first installment of this series, we scraped reviews from Goodreads. In thesecond one, we performed exploratory data analysis and created new v
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