In this research, we present and analyze techniques that predict students' final outcome (with respect to grade) for a particular course. We validate our method by conducting experiments on data that are related to grade for courses in North South University, one of the leading universities in ...
In this research, we present and analyze techniques that predict students’ final outcome (with respect to grade) for a particular course. We vali-date our method by conducting experiments on data that are related to grade for courses in North South University, one of the leading universities ...
With a bin size too large, the time dependency of the firing rate is lost, and with a bin size too small, the fluctuations in the estimation might be too rapid (Hardle and Abbott, 1991). Shimazaki and Shinomoto (2007) proposed a method to optimize the bin size of the time histogram ...
Metagenomics provides a culture-free method to study microorganisms by directly analyzing genomes and genes collected from microbial populations1and mining important information related to the environment and human diseases2,3,4. Corresponding computational methods have been developed rapidly in the past two...
Methods The approach of our binning method is outlined in Figure 2. First, the l-mer occurrence frequencies of each DNA fragment in the sample are counted. Not all l-mers will be used in the classification process. We have a simple, but effective method, based on our novel modified ...
Despite recent advances in metagenomic binning, reconstruction of microbial species from metagenomics data remains challenging. Here we develop variational autoencoders for metagenomic binning (VAMB), a program that uses deep variational autoencoders to
In these pathogens, analysis of genome architecture has assisted the mining for novel candidate effector genes and investigations into patterns of gene regulation and evolution at the whole genome level. Here we describe a two-dimensional data binning method in R with a heatmap-style graphical ...
1. Describe credit scoring and explain how it s used (by lenders) in making a credit decision. 2. Describe the basic operations and functions of a credit bureau. 3. What is the most common method us What are two techniques that you could use to develop a rough estimate for ...
The machine learning analysis method we employed on these data was a specific type of neural network, a Self-Organizing Map (SOM, also known as a Kohonen network) that performs very effective supervised and unsupervised clustering of large, complex ToF-SIMS data sets. These computational studies ...
Thus, we found the RF model, followed by viralVerify, to be the best-suited method on bin-level in mixed-organism assembly datasets. While the RF model predicts plasmids incorrectly as viral, we found that the downstream use of CheckV helped in making a final con- fident evaluation as ...