A data science project using ... challenges. Python library to handle Scanning Probe Microscopy Images. Can read nanoscan .xml data, Bruker AFM images, Nanonis SXM files as well as iontof images(ITA, ...

Guangxi Colleges and Universities Key Laboratory of Data Analysis ... indicators using the entropy weight method, and established a bank efficiency evaluation formula to determine the failure ...

Orange Data Mining is a Python ... Principal component analysis (PCA) is one of the most common exploratory data analysis techniques with applications in outlier detection, dimensionality reduction, ...

The authors present a critique of current usage of principal component analysis in geometric ... and reproducibility using benchmark data of the crania of five papionin genera, we developed MORPHIX, a ...

The larger data requires correspondingly fast computer-based analyses. However, these analyses often do not scale well with increased data size. Principal component analysis (PCA ... We show that ...

Principal component analysis (PCA) is a classical machine ... A "true" argument means the data variables are organized as rows. I use this interface to match that of the Python numpy.cov() library ...

Principal Component Analysis (PCA) is a statistical technique for reducing the dimensionality of a dataset while preserving as much variability as possible. It transforms the data into a new ...