標題: Titlebook: Applied Statistical Learning; With Case Studies in Matthias Schonlau Textbook 2023 The Editor(s) (if applicable) and The Author(s), under e [打印本頁] 作者: Intermediary 時間: 2025-3-21 18:28
書目名稱Applied Statistical Learning影響因子(影響力)
書目名稱Applied Statistical Learning影響因子(影響力)學科排名
書目名稱Applied Statistical Learning網絡公開度
書目名稱Applied Statistical Learning網絡公開度學科排名
書目名稱Applied Statistical Learning被引頻次
書目名稱Applied Statistical Learning被引頻次學科排名
書目名稱Applied Statistical Learning年度引用
書目名稱Applied Statistical Learning年度引用學科排名
書目名稱Applied Statistical Learning讀者反饋
書目名稱Applied Statistical Learning讀者反饋學科排名
作者: 明智的人 時間: 2025-3-21 20:25
Basak Kalkanci,Erjie Ang,Erica L. PlambeckWe discuss who should read this book, book structure, where Stata is used, data sets and comments for instructors.作者: 乞討 時間: 2025-3-22 00:47
Environmentally-Friendly Product DevelopmentWe briefly introduce stacking as a way of combining predictions from several learning algorithms. Winning entries in Kaggle competitions often use some form of stacking.作者: 同音 時間: 2025-3-22 08:31 作者: anagen 時間: 2025-3-22 12:42 作者: neuron 時間: 2025-3-22 15:30
Matthias SchonlauThe first book to present statistical/machine learning with case studies using Stata.Provides numerous conceptual exercises, exercises that require software, and case studies.Introduces neural network作者: GILD 時間: 2025-3-22 18:00
Statistics and Computinghttp://image.papertrans.cn/b/image/160152.jpg作者: GREG 時間: 2025-3-22 23:24 作者: 投射 時間: 2025-3-23 05:06 作者: 不足的東西 時間: 2025-3-23 09:19
Environmentally Sustainable ProductionA case study discusses pharmacy compliance with a California Senate Bill as a function of various covariates. The case study illustrates ROC curves, AUC values, accuracy, sensitivity, specificity, and other evaluation measures. Finally, we point out logistic can be surprisingly hard to beat for pred作者: Mindfulness 時間: 2025-3-23 13:26
Environmentally Sustainable Productionaussian linear regression, choosing an L2 penalty leads to ridge regression and choosing an L1 penalty leads to the Lasso. The same penalties can be applied to logistic regression. Both penalties tend to reduce the magnitude of coefficients. Because the L1 penalty can reduce coefficients to zero, th作者: delta-waves 時間: 2025-3-23 16:54
https://doi.org/10.1007/978-3-031-52656-5 often a given word appears in each text. A bigram variable counts how often a sequence of two words appears in each text. Such n-gram variables lead to a large number of variables. The data are also sparse –most entries are zero– because most words do not appear in most texts. The use of stemming, 作者: Grating 時間: 2025-3-23 20:49
Environmentally Sustainable Productions that can arise for prediction. kNN can easily accommodate highly nonlinear behavior and approximates the Bayes classifier. However, kNN is slow for large data sets and memory hungry. The tuning parameter . regulates the bias-variance tradeoff, and kNN is sensitive to scaling. The case study classi作者: 閃光東本 時間: 2025-3-24 01:09 作者: pus840 時間: 2025-3-24 05:26 作者: apropos 時間: 2025-3-24 06:41 作者: ALERT 時間: 2025-3-24 13:54 作者: 向下五度才偏 時間: 2025-3-24 17:17 作者: 傳授知識 時間: 2025-3-24 21:57 作者: –FER 時間: 2025-3-25 01:32
Environmentally-Friendly Product Developmentor regression and multi-class classification. We discuss a number of common activation functions that contribute nonlinearity in an otherwise linear network. We cover vanishing and exploding gradients, weight initialization—to attenuate the vanishing gradient problem—stochastic gradient descent usin作者: SAGE 時間: 2025-3-25 05:41
https://doi.org/10.1007/978-3-031-33390-3Statistical Learning; Machine Learning; Stata; Applications in the Social Sciences; Case Studies; Text Da作者: gnarled 時間: 2025-3-25 10:09 作者: 圣歌 時間: 2025-3-25 15:08
Textbook 2023s of data science in the field. Although mainly intended for upper undergraduate and graduatestudents in the social sciences, given its applied nature, the book will equally appeal to readers from other disciplines, including the health sciences, statistics, engineering and computer science..作者: 制定法律 時間: 2025-3-25 18:34 作者: 先兆 時間: 2025-3-25 22:39
Statistical Learning: Concepts,f interpretation and prediction. We introduce the bias-variance tradeoff as a central theme in statistical learning. Next, we introduce the Bayes error as the lowest possible error. The Bayes error is of limited use in practice because it requires knowledge of the true functional relationship betwee作者: 漂亮才會豪華 時間: 2025-3-26 03:34
Statistical Learning: Practical Aspects,cause the true functional relationship is unknown in practice, the Bayes error cannot be computed. Instead, we use different subsets of the data for training and evaluation. There are several techniques for splitting the data into subsets for this purpose. One such technique, cross-validation, uses 作者: Gratulate 時間: 2025-3-26 08:12 作者: Ventilator 時間: 2025-3-26 09:14
Lasso and Friends,aussian linear regression, choosing an L2 penalty leads to ridge regression and choosing an L1 penalty leads to the Lasso. The same penalties can be applied to logistic regression. Both penalties tend to reduce the magnitude of coefficients. Because the L1 penalty can reduce coefficients to zero, th作者: allergen 時間: 2025-3-26 14:15 作者: 擺動 時間: 2025-3-26 19:57 作者: calumniate 時間: 2025-3-27 00:39
The Naive Bayes Classifier,sifier the designation “naive.” The assumption greatly simplifies calculations; the naive Bayes classifier is very fast. The assumption trades off increased bias with reduced variance making the classifier surprisingly successful. The Naive Bayes classifier often benefits from smoothing. We discuss 作者: defendant 時間: 2025-3-27 02:18 作者: 爭論 時間: 2025-3-27 07:31
Random Forests,ition, at each split, random forests only consider a random subset of x-variables. This promotes the use of a larger number of x-variables and makes the algorithm less dependent on a small number of variables. For any one tree, roughly one third of the observations are not in the bootstrap sample an作者: 嘮叨 時間: 2025-3-27 12:48
Boosting,g. We talk about variable influence as a way of computing the contribution of individual variables and contrast this approach with variable importance as used in random forests. We discuss tuning parameters and the effect of individual tuning parameters on computing time. We also introduce an increa作者: 流浪 時間: 2025-3-27 16:31
Support Vector Machines, line and the nearest observation of either class is maximized. Often the classes are not separable, i.e., they do not form separate clouds in x-space. In that case, a cost parameter allows for a certain amount of classification error. By deriving additional x-variables (e.g., quadratic terms), we c作者: aristocracy 時間: 2025-3-27 21:04 作者: guardianship 時間: 2025-3-27 22:42
Neural Networks,or regression and multi-class classification. We discuss a number of common activation functions that contribute nonlinearity in an otherwise linear network. We cover vanishing and exploding gradients, weight initialization—to attenuate the vanishing gradient problem—stochastic gradient descent usin作者: 分散 時間: 2025-3-28 03:29 作者: 帽子 時間: 2025-3-28 09:43 作者: transplantation 時間: 2025-3-28 14:00 作者: anus928 時間: 2025-3-28 17:11
https://doi.org/10.1007/978-3-031-52656-5removal of stopwords, and employing thresholds reduce the number of variables somewhat. A case study categorizes answers from an open-ended survey question (in German) about respondents’ beliefs about immigrants.作者: brachial-plexus 時間: 2025-3-28 22:46 作者: 駭人 時間: 2025-3-29 01:43
Environmentally-Friendly Product Developmentd form an out-of-bag sample. For a given tree, the out-of-bag sample can be used as validation sample, giving the algorithm the unique ability to tune parameters without a separate validation sample. This is particularly useful when the training data available are limited. A case study predicts math achievement of Portuguese high school students.作者: 正面 時間: 2025-3-29 03:49 作者: 噴油井 時間: 2025-3-29 08:30 作者: GRUEL 時間: 2025-3-29 13:17
Environmentally Sustainable Productionng a parameter gives rise to a U-shaped error curve. This echoes the earlier discussion in Chap. . related to U-shaped and bias-variance tradeoff. In addition, we also discuss different evaluation criteria, one-hot encoding, variable scaling and reproducibility.作者: Cholesterol 時間: 2025-3-29 18:55 作者: Foregery 時間: 2025-3-29 23:33 作者: 悅耳 時間: 2025-3-30 02:25
Environmentally-Friendly Product Developmentobservations appear more sparse in higher dimensions. The so-called kernel trick makes expanding the x-space computationally efficient. Support vector classification can be adapted to work for multi-class and regression problems. A case study predicts the popularity of online news.作者: 討好美人 時間: 2025-3-30 04:38
Statistical Learning: Practical Aspects,ng a parameter gives rise to a U-shaped error curve. This echoes the earlier discussion in Chap. . related to U-shaped and bias-variance tradeoff. In addition, we also discuss different evaluation criteria, one-hot encoding, variable scaling and reproducibility.作者: TATE 時間: 2025-3-30 12:15
The Naive Bayes Classifier, be classified as a history, tragedy, or comedy, had the movie been written by Shakespeare. Our case study is about an open-ended survey question where respondents give advice to “Patient Joe” in a hypothetical situation. We classify the text answers into one of four classes.作者: leniency 時間: 2025-3-30 13:48 作者: 交響樂 時間: 2025-3-30 19:45
Support Vector Machines,observations appear more sparse in higher dimensions. The so-called kernel trick makes expanding the x-space computationally efficient. Support vector classification can be adapted to work for multi-class and regression problems. A case study predicts the popularity of online news.
