Search results for "Python"
showing 10 items of 160 documents
Daudzspēlētāju kāršu spēle
2015
Kvalifikācijas darbs apraksta kāršu spēles izveidi. Spēles funkcionalitāte ietver lokālu spēli, datora pretinieku. Spēles aprakstā ietilpst daudzspēlētāju režīma projektējums. Programmai ir grafiska lietotāja saskarne. Tā veidota python programmēšanas valodā, ar pyglet grafiskās bibliotēkas palīdzību. Darbs sevī ietver spēles dokumentāciju un pašu programmu.
Corrigendum: ExGUtils: A Python Package for Statistical Analysis With the ex-Gaussian Probability Density
2018
Pacientu komentāru nolūka noteikšana izmantojot mašīnmācīšanos
2020
Bakalaura darba mērķis ir automatizēt procesu aptauju atvērtā tipa jautājumu nolūka noteikšanai, izmantojot uzraudzīto mašīnmācīšanos, kā arī pierādīt izvēlētā risinājuma veiktspēju. Programmatūras risinājums paredzēts pacientu komentāru nolūka noteikšanai. Bakalaura darbs sastāv no vārdnīcas, ievada, mašīnmācīšanās teorijas, eksistējošiem risinājumiem, mašīnmācīšanās bibliotēku analīzi, datu apstrādes, modeļa parametru izklāsta, modeļa izstrādes, rezultātiem, secinājumiem, izmantotās literatūras un pielikumiem. Bakalaura darbā aprakstītas mašīnmācīšanās bibliotēkas, ko iespējams izmantot risinājuma izstrādei. Ar konkrētu izvelētu mašīnmācīšanās bibliotēku aprakstīta mašīnmācīšanās modeļa i…
Interpretable machine learning models for single-cell ChIP-seq imputation
2019
AbstractMotivationSingle-cell ChIP-seq (scChIP-seq) analysis is challenging due to data sparsity. High degree of data sparsity in biological high-throughput single-cell data is generally handled with imputation methods that complete the data, but specific methods for scChIP-seq are lacking. We present SIMPA, a scChIP-seq data imputation method leveraging predictive information within bulk data from ENCODE to impute missing protein-DNA interacting regions of target histone marks or transcription factors.ResultsImputations using machine learning models trained for each single cell, each target, and each genomic region accurately preserve cell type clustering and improve pathway-related gene i…
PyDSC: a simple tool to treat differential scanning calorimetry data
2020
AbstractHerein, we describe an open-source, Python-based, script to treat the output of differential scanning calorimetry (DSC) experiments, called pyDSC, available free of charge for download at https://github.com/leonardo-chiappisi/pyDSC under a GNU General Public License v3.0. The main aim of this program is to provide the community with a simple program to analyze raw DSC data. Key features include the correction from spurious signals, and, most importantly, the baseline is computed with a robust, physically consistent approach. We also show that the baseline correction routine implemented in the script is significantly more reproducible than different standard ones proposed by propriet…
Challenges of automatic processing of large amount of skin lesion multispectral data
2020
This work will describe the challenges involved in setting up automatic processing for a large differentiated data set. In this study, a multispectral (skin diffuse reflection images using 526nm (green), 663nm (red), and 964nm (infrared) illumination and autofluorescence (AF) image using 405 nm excitation) data set with 756 lesions (3024 images) was processed. Previously, using MATLAB software, finding markers, correctly segmenting images with dark edges and image alignment were the main causes of the problems in automatic data processing. To improve automatic processing and eliminate the use of licensed software, the latter was substituted with the open source Python environment. For more …
On Multiresolution Transforms Based on Weighted-Least Squares
2014
This work is devoted to construct Harten’s multiresolution transforms using Weighted-Least squares for different discretizations. We establish a relation between the filters obtained using some decimation operators. Some properties and examples of filters are presented.
Papildu funkciju izstrāde mašīnmācīšanās teksta analizatoram
2019
Teksta analīzes veikšanai ir pieejamas vairākas metodes, šajā dokumentā ir apskatīts kā pielietot Correlation Explanation[7] (korelāciju skaidrošana, turpmāk CorEx[7]) teksta analīzes metodi, implementējot atvērtā pirmkoda (open-source) bibliotēku corextopic[3], jau izstrādātā sistēmā - mašīnmācīšanās teksta analizatorā (turpmāk MMTA). Darbā ir aprakstīta MMTA pamatdarbība un tā mijiedarbība ar implementēto corextopic[3] bibliotēku. MMTA ir programmprodukts ar implementētām vairākām bibliotēkām, kas dod iespēju programmprodukta lietotājam izvēlēties starp vairākām datu apstrādes metodēm saistībā ar teksta analīzi. MMTA darbība iedalās. Informācijas ekstrakcija un tēmu modelēšana ir divi MMT…
Implications of quantum automata for contextuality
2014
We construct zero error quantum finite automata (QFAs) for promise problems which cannot be solved by bounded error probabilistic finite automata (PFAs). Here is a summary of our results: There is a promise problem solvable by an exact two way QFA in exponential expected time but not by any bounded error sublogarithmic space probabilistic Turing machine (PTM). There is a promise problem solvable by an exact two way QFA in quadratic expected time but not by any bounded error o(loglogn) space PTMs in polynomial expected time. The same problem can be solvable by a one way Las Vegas (or exact two way) QFA with quantum head in linear (expected) time. There is a promise problem solvable by a Las …
Predictive Model Markup Language (PMML) Representation of Bayesian Networks: An Application in Manufacturing
2018
International audience; Bayesian networks (BNs) represent a promising approach for the aggregation of multiple uncertainty sources in manufacturing networks and other engineering systems for the purposes of uncertainty quantification, risk analysis, and quality control. A standardized representation for BN models will aid in their communication and exchange across the web. This article presents an extension to the predictive model markup language (PMML) standard for the representation of a BN, which may consist of discrete variables, continuous variables, or their combination. The PMML standard is based on extensible markup language (XML) and used for the representation of analytical models…