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Regularized regression
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Part 1 of ebook "The elements of statistical learning: Data mining, inference, and prediction (Second edition)" provides readers with contents including: Chapter 1 - Introduction; Chapter 2 - Overview of supervised learning; Chapter 3 - Linear methods for regression; Chapter 4 - Linear methods for classification; Chapter 5 - Basis expansions and regularization; Chapter 6 - Kernel smoothing methods; Chapter 7 - Model assessment and selection; Chapter 8 - Model inference and averaging; Chapter 9 - Additive models, trees, and related methods;...
355p
daonhiennhien
03-07-2024
2
1
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Reproductive health service (RHS) helps for people to have a delighted and safe sex through their life journey. It enables especially for women to go safely through pregnancy and childbirth and provide couples with the best chance of having a healthy infant. Therefore, this study aimed to identify the significant determinants of RHS utilization among undergraduate regular class students in Assosa University by using advanced methodology.
10p
vishanshan
27-06-2024
1
1
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This study work was conducted to determine whether eating habits could serve as an alternative medication in reducing blood pressure among hypertensive patients. Information was collected on patients with hypertension cases who were advised to be taking regular diets and avoid some types of feeding, such as starchy foods, foods with cholesterols and drinking alcohol.
9p
vikissinger
21-12-2023
3
1
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Over the past decades, the prevalence of type 2 diabetes mellitus (T2D) has been steadily increasing around the world. Despite large efforts devoted to better understand the genetic basis of the disease, the identified susceptibility loci can only account for a small portion of the T2D heritability.
12p
vinarcissa
21-03-2023
4
1
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Lecture Introduction to Machine learning and Data mining: Lesson 10. This lesson provides students with content about: regularization; revisiting overfiting; the bias-variance decomposition; bias-variance tradeoff; regularization in ridge regression; regularization in lasso;... Please refer to the detailed content of the lecture!
25p
hanlamcoman
26-11-2022
10
5
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Part 1 of the document "Speech and language processing: An introduction to natural language processing, computational linguistics, and speech recognition" provide with knowledge about: regular expressions, text normalization, edit distance; N-gram language models; naive bayes and sentiment classification; logistic regression; vector semantics and embeddings; neural networks and neural language models;...
287p
britaikridanik
05-07-2022
17
6
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Single-cell RNA-seq (scRNA-seq) data exhibits significant cell-to-cell variation due to technical factors, including the number of molecules detected in each cell, which can confound biological heterogeneity with technical effects. To address this, we present a modeling framework for the normalization and variance stabilization of molecular count data from scRNA-seq experiments.
15p
vielonmusk
30-01-2022
8
0
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Results from multivariate regressions showed that regular use of SM for entertainment purposes was a predictor that hinders creative behavior, whereas using SM for academic, socialization, and informativeness purposes did not significantly predict creative behavior.
20p
mudbound
06-12-2021
11
1
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A concomitant tibial shaft and posterior malleolar fracture is a type of regular compound fracture. The associated posterior malleolar fractures are mostly occult fractures, which often do not show a fracture line on ordinary films, and thus lead to a high rate of misdiagnosis.
8p
vitennessee2711
02-02-2021
12
2
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This paper gives a literature review of choosing tuning parameters for ridge regression and lasso. These regularized regressions introduce a little bias in return for a considerable decrease in the variance of the predicted values, thus increasing prediction accuracy. This paper can use AIC or BIC to select the tuning parameter for linear predictive models.
16p
angicungduoc9
04-01-2021
6
2
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Microarray technology is widely used in cancer diagnosis. Successfully identifying gene biomarkers will significantly help to classify different cancer types and improve the prediction accuracy. The regularization approach is one of the effective methods for gene selection in microarray data, which generally contain a large number of genes and have a small number of samples.
12p
viwyoming2711
16-12-2020
9
1
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A growing number of crystal and NMR structures reveals a considerable structural polymorphism of DNA architecture going well beyond the usual image of a double helical molecule. DNA is highly variable with dinucleotide steps exhibiting a substantial flexibility in a sequence-dependent manner.
14p
viwyoming2711
16-12-2020
7
1
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High-dimensional molecular measurements, e.g. gene expression data, can be linked to clinical time-to-event endpoints by Cox regression models and regularized estimation approaches, such as componentwise boosting, and can incorporate a large number of covariates as well as provide variable selection.
12p
vikentucky2711
24-11-2020
10
1
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To facilitate advances in personalized medicine, it is important to detect predictive, stable and interpretable biomarkers related with different clinical characteristics. These clinical characteristics may be heterogeneous with respect to underlying interactions between genes.
18p
vioklahoma2711
19-11-2020
11
1
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Threshold regression models are a diverse set of non-regular regression models that all depend on change points or thresholds. They provide a simple but elegant and interpretable way to model certain kinds of nonlinear relationships between the outcome and a predictor.
7p
viconnecticut2711
29-10-2020
32
0
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Breast and prostate cancers are typical examples of hormone-dependent cancers, showing remarkable similarities at the hormone-related signaling pathways level, and exhibiting a high tropism to bone.
15p
vijisoo2711
27-10-2020
12
0
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The standard lasso penalty and its extensions are commonly used to develop a regularized regression model while selecting candidate predictor variables on a time-to-event outcome in high-dimensional data.
20p
vicolorado2711
22-10-2020
6
0
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Understanding cellular and molecular heterogeneity in glioblastoma (GBM), the most common and aggressive primary brain malignancy, is a crucial step towards the development of effective therapies. Besides the inter-patient variability, the presence of multiple cell populations within tumors calls for the need to develop modeling strategies able to extract the molecular signatures driving tumor evolution and treatment failure.
12p
vicolorado2711
22-10-2020
15
1
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This paper presents the results of water use situation, Willingness-To-Pay (WTP) and analysis of the factors affecting WTP for water service of residents in Vinh Xuan. The objective of the paper is to evaluate the status of clean water use and people’s awareness through WTP for water service. A survey on water consumption and WTP estimation of users for water service experienced that only one-third of Vinh Xuan people have had access to clean water. This situation illustrated getting access as well as using clean water have been still limited while the demand of water use has been rising.
8p
angicungduoc5
13-06-2020
17
0
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This lecture will teach you how to fit nonlinear functions by using bases functions and how to control model complexity. The goal is for you to: Learn how to derive ridge regression; understand the trade-off of fitting the data and regularizing it; Learn polynomial regression; understand that, if basis functions are given, the problem of learning the parameters is still linear; learn cross-validation; understand model complexity and generalization.
28p
allbymyself_08
22-02-2016
51
4
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