Artificial intelligence is rapidly changing the job market, automating jobs across industries. Therefore, in such a scenario, upskilling oneself in industry-relevant AI skills becomes even more ...
Abstract: This work aims to compare two different Feature Extraction Algorithms (FEAs) viz. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), using a K-Nearest Neighbor (KNN) ...
In the rapidly advancing field of ‘omics research, there is an increasing demand for sophisticated bioinformatic tools to enable efficient and consistent data analysis. As biological datasets, ...
Implementing PCA (Principal Component Analysis) from scratch for Dimensionality Reduction which is Reducing the number of input variables for a predictive model ...
The input data is preprocessed with the Scanpy package in Python. Starting from the raw gene-cell count matrix, library size normalization is performed to scale the total counts of each cell to be ...
Hospitals across the country are using software powered by algorithms with racial biases, according to a new report from a coalition of healthcare providers. This can cause physicians to misdiagnose ...
Abstract: K-nearest neighbor (KNN) algorithm is a simple and widely used classification method in machine learning. This algorithm tries to search every object in the dataset to find the nearest ...
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