搜索结果: 1-15 共查到“知识库 相关回归分析”相关记录36条 . 查询时间(0.703 秒)
带特定标记的分位数回归模型
特定标记 分位数 回归模型
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2023/12/13
在许多现实的机器学习应用场景中,获取大量未标注的数据是很容易的,但标注过程需要花费大量的时间和经济成本.因此,在这种情况下,需要选择一些最有价值的样本进行标注,从而只利用较少的标注数据就能训练出较好的机器学习模型。
基于逻辑回归函数的加权K-means聚类算法
欧式距离 特征加权的K-means算法 逻辑回归函数 初始聚类中心
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2022/3/15
股票信息挖掘与LSTM预测
股票预测 长短时记忆神经网络(LSTM) 回归分析
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2022/3/23
基于符号回归的产品评论数量与购买数量关系分析
购买数量 评论数量 关系模型 符号回归方法
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2022/3/25
ADAPTIVE SPLINE ESTIMATES FOR NONPARAMETRIC REGRESSION MODELS
ADAPTIVE SPLINE ESTIMATES NONPARAMETRIC REGRESSION MODELS
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2015/8/25
ADAPTIVE SPLINE ESTIMATES FOR NONPARAMETRIC REGRESSION MODELS.
Least Angle Regression
Least Angle Regression
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2015/8/21
The purpose of model selection algorithms such as All Subsets, Forward Selection, and Backward Elimination is to choose a linear model on the basis of the same set of data to which the model will be a...
Prediction by Supervised Principal Components
Gene expression Microarray Regression Survival analysis
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2015/8/21
In regression problems where the number of predictors greatly exceeds the number of observations, conventional regression techniques may produce unsatisfactory results. We describe a technique called ...
Forward stagewise regression and the monotone lasso
regression lasso stagewise
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2015/8/21
We consider the least angle regression and forward stagewise algorithms for solving penalized least squares regression problems. In Efron,Hastie, Johnstone & Tibshirani (2004) it is proved that the le...
PATHWISE COORDINATE OPTIMIZATION
Coordinate descent lasso convex optimization
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2015/8/21
We consider “one-at-a-time” coordinate-wise descent algorithms for a class of convex optimization problems. An algorithm of this kind has been proposed for the L1-penalized regression (lasso) in the l...
Genomewide Association Analysis by Lasso Penalized Logistic Regression
Genomewide Association Analysis Lasso Penalized Logistic Regression
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2015/8/21
In ordinary regression, imposition of a lasso penalty makes continuous model selection straightforward. Lasso penalized regression is particularly advantageous when the number of predictors far exceed...
Strong Rules for Discarding Predictors in Lasso-type Problems
Strong Rules Discarding Predictors Lasso-type Problems
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2015/8/21
We consider rules for discarding predictors in lasso regression and related problems, for computational efficiency. El Ghaoui et al. (2010) propose “SAFE” rules, based on univariate inner products bet...
Detecting changes in functional linear models
functional data projections weak dependence change point weak convergence
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2011/6/15
We observe two sequences of curve which are connected via an integral operator. Our model includes linear models as well as autoregressive models in Hilbert spaces. We wish to test the null hypothesis...
Confidence Sets in Time--Series Filtering
Confidence Sets Time--Series Filtering
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2011/1/21
The problem of filtering of finite–alphabet stationary ergodic time series is considered. A method for constructing a confidence set for the (unknown) signal is proposed.
The Hannan-Quinn Proposition for Linear Regression
Hannan-Quinn linear regression the law of iterated logarithms strong consistency
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2011/2/23
We consider the variable selection problem in linear regression. Suppose that we have a set
of random variables X1, · · · ,Xm, Y, ǫ such that Y = Pk2 αkXk +ǫ with π ⊆ {1, · · · ,m} a...