elayden Goto Github PK
Name: Elliot Layden
Type: User
Bio: Neuroscience/Psychology PhD --> Data Scientist
Location: Seattle, WA
Elliot Layden's Projects
cohenskappa
Matlab function computes Cohen's kappa from observed categories and predicted categories
deep-learning-framework-for-financial-time-series-prediction-in-python-keras
Randomly partitions time series segments into train, development, and test sets; Trains multiple models optimizing parameters for development set, final cross-validation in test set; Calculates model’s annualized return, improvement from buy/hold, percent profitable trades, profit factor, max drawdown
elayden.github.io
Personal website
example-scalping
A working example algorithm for scalping strategy trading multiple stocks concurrently using python asyncio
fmri-preprocessing-with-advanced-normalization-tools
A simple, customizable pipeline for preprocessing resting-state or task-based functional MRI data sets.
mriqual
A Matlab toolbox for examining the quality of structural (SNR) and functional (tSNR, SFNR) MRI
n-back-for-matlab
The classic dual n-back task implemented in Matlab; includes position, sound, and color options.
n-back-mri
The dual n-back task implemented in Matlab with precise timing for use within the MRI scanner.
nifti-studio
A toolbox for NIfTI and Analyze medical image visualization, editing, and 3D rendering
plot-corrmat
A Matlab utility for plotting correlation matrices, with similar appearance to Seaborn in Python.
portfolio_sharpe_ratio
This Matlab package optimizes portfolio weights based on Sharpe ratio, average total return, and volatility.
portfolio_sortino_ratio
This function optimizes portfolio weights based on a user-specified weighted linear combination of the Sortino ratio, Sharpe ratio, average total return, average downside risk, average standard deviation of returns, and max drawdown.
roi_overlap
Matlab function that calculates and outputs a table showing the percentage overlap between statistical clusters and brain atlas regions (AAL, Harvard-Oxford, Brodmann Areas)
selectfeatures
Improved sequential feature selection for linear or quadratic discriminant analysis.
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