Ram´irez-Quintana. Binarised regression tasks: Meth- ods and evaluation metrics. Data Mining and Knowledge Dis- covery, 30(4):848-890, 2016.Hernandez-Orallo, J., Ferri, C., Lachiche, N., Martinez-Uso, A., and Ramirez-Quintana, M. J. (2016). Binarised regression tasks: methods and evaluation metrics. Data Mining and ...
In this post, I focus on metrics used to evaluate regression problems involved in predicting a numeric value—be it the price of a house or a forecast for next month’s company sales. As regression analysis can be considered the foundation of data science, it is essential to understand the...
In this section, we present the implementation of BiDLSTM and discuss the experimental findings. We compare the model’s performance with state-of-the-art methods trained and tested on the same dataset (i.e., the NSL-KDD dataset). Also, we present a comparison of results with some recently...
27k Accesses 6 Altmetric Metrics details Abstract Transcriptome deconvolution aims to estimate the cellular composition of an RNA sample from its gene expression data, which in turn can be used to correct for composition differences across samples. The human brain is unique in its transcriptomic diver...
First, it provides a comprehensive collection of metrics for the evaluation of recommender systems. Second, it includes a variety of methods for reporting and plotting the performance results. Implemented metrics cover a range of well-known metrics and newly proposed metrics from data mining (ICDM,...
Regression methods for analyzing RNA-Seq data Negative binomial (NB) regression NB regression uses the Maximum-Likelihood (ML) fitting process [26]. The generalized linear model (GLM) framework is used by DESeq2 and edgeR. In the current study, GLM was implemented using theglm(,family =...
Methods of frequentist based indirect comparison have been investigated in several previous simulation studies [1, 20, 21]. A study found that the Bucher’s method and logistic regression generally provided unbiased estimates [1]. The simulation scenarios evaluated in that study was limited by using...
Utility function for train() and eval() methods. Not intended to be used directly compute_metrics(self, preds, labels, eval_examples, **kwargs): Computes the evaluation metrics for the model predictions. Args: preds: Model predictions labels: Ground truth labels eval_examples: List of ...
The evaluation of task-oriented dialogue systems is built around the structured nature of the interaction. Two main aspects are evaluated, which have been shown to define the quality of the dialogue: task-success and dialogue efficiency. Two main metrics of evaluation methods have been proposed: ...
Relevance networks postulate that genes included in It should be strongly correlated with TFt, therefore MA and DM methods are evaluated with respect to their ability of assigning highly significant correlations to known interactions. Different metrics are used to com- pare each Ct,X against its ...