arek-kesizabnousi Goto Github PK
Name: Arek Kesiz Abnousi
Type: User
Bio: https://www.linkedin.com/in/arek-kesiz-abnousi/
Arek Kesiz Abnousi's Projects
covid-19-cases-modeling-via-splines
we fit various splines to model the COVID-19 daily positive case numbers in Florida from 3/3/20 – 3/7/21.
gae
Implementation of Graph Auto-Encoders in TensorFlow
glmm--gee
Generalized linear mixed model (GLMM) and Generalized estimating equation (GEE)
gradient_boosting-vs-superlearner
Implementing Gradient Boosting & SuperLearner in R and compare the classification accuracy of the two methods.
large-covariance-matrices_estimators
Comparing three different Generalized Thresholding Estimators For Large Covariance Matrices. soft-thresholding, hard-thresholding, and adaptive-soft-thresholding Estimators.
lasso-vs-leastangleregression
Code of the least angle regression solution path by hand for an example( p=5). Then we compute the solution path for a dataset and compare it with the LASSO path.
lasso-vs-scad-vs-mcp_estimators
Comparing Three Penalized Least Squares Estimators: LASSO,SCAD and MCP.
linear_graph_autoencoders
Source code from the NeurIPS 2019 workshop article "Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks" (G. Salha, R. Hennequin, M. Vazirgiannis) + k-core framework implementation from IJCAI 2019 article "A Degeneracy Framework for Scalable Graph Autoencoders" (G. Salha, R. Hennequin, V.A. Tran, M. Vazirgiannis)
neural_networks
Fit four different neural networks: (a) Two distinct single hidden layer neural networks. (b) Two distinct neural networks with two hidden layers. Compare the accuracy of these four Neural networks among them. Also compare it to other classification methods.
random_forest
Tuning Random Forests, comparing their classification accuracy to Regression Trees.
reinforcement_learning-python
We use python software and NumPy library to implement the Q-learning method , train an Agent to solve a Reinforcement Learning Problem
support_vector_machines-vs-discriminant_analysis
Comparing Classification Methods. We will code some Discriminant Analysis Methods and compare them to Support Vector Machines (SVMs).
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