Machine learningFinancial fraudMeta-ClassifiersVoting-ClassifierStacked-ClassifierWe develop Meta-Classifiers to detect financial frauds by combining several accurate and diverse stand-alone classifiers. Our results suggest that the Meta-Classifiers developed in our study can outperform the best stand-alone ...
In order to induce a meta classifier, first the base classifiers are trained (stage one), and then the Meta classifier (second stage). In the prediction phase, base classifiers will output their classifications, and then the Meta-classifier(s) will make the final classification (as a function...
适应性可以理解为,给定训练数据集训练的模型,却可以接近类似的不同的问题的能力。 换言之, 元学习是 让模型具有接近新task的能力, 也可以称之为learning to learn。 一下提供两个简单的例子来理解什么是元学习: 一个分类器(classifier)只在没有猫咪的图片集上进行了训练,但是输入一张猫咪的图片可以分辨此图是否...
Meta-learning可以理解为一种求解问题的工具,下面举一个例子,通俗的说明meta-learning的作用。在正常的machine learning中,需要将数据集分成trainset和testset,模型在trainset上进行训练,在testset上评测效果。但是,在trainset上的训练过程可能导致过拟合,进而引起在testset上效果较差。如何才能设计一种面向testset上效果...
We formulate the adaptation as an estimation problem of the Bayes optimal classifier, which is an optimal classifier to minimize the classification risk. The proposed method embeds each instance into a task-specific space using neural networks. With the embedded PU data, the Bayes optimal classifier...
The overall resulting classifier is composed of the classifiers generated by the different learning algorithms and a meta-classifier generated by a meta-learning strategy. The strategies described here are independent of the learning algorithms used. Preliminary experiments using different strategies and ...
Meta-learning, or learning to learn, is the science of systematically observing how different machine learning approaches perform on a wide range of learning tasks, and then learning from this experience, or meta-data, to learn new tasks much faster than
This parameter can be one of the following strings: LogisticRegression, LogisticRegressionCV, LightGBMClassifier, ElasticNet, ElasticNetCV, LightGBMRegressor, or LinearRegression. Inheritance builtins.str StackMetaLearnerType Enum StackMetaLearnerType Constructor Python コピー S...
meta-learning虽然目的是learning to learn，但是其问题设定和few-shot的设定在我们看来是一种父类和子类...
我们希望元学习器 (meta-learner) 可以学会学习 (learning to learn), 即一个成熟的元学习器在少量样本的前提下拥有快速泛化到不同任务的能力, 如下图所示. 图4: 元学习过程 那么如何训练这样的元学习器呢? 以分类任务为例: Common ClassifierMeta-Learner 训练集 包含多种类别 包含多种分类任务 测试样本 一...