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Thinking about science (and doing science).
- New York, New York
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Use monte-carlo subsampling to compu...
Use monte-carlo subsampling to compute a summary population statistic for frequency distribution 1"""
2This package includes a method to compute the observed test-statistic and assocated pvalue
3"""
45import json
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Custom-built pytorch model to do mas...
Custom-built pytorch model to do massive, end-to-end MIL for whole-slide imaging data 1import torch
2from torch import nn
3from torch.nn import init
4from torch.nn import functional as F
5from torch.autograd import Function
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robo-trader
robo-trader PublicCollection of services, exploratory analysis to support algorithmic stock trading
Jupyter Notebook
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Generates a nice AUC plot given a li...
Generates a nice AUC plot given a list of labels and scores, with an average and standard deviation shown, optionally merging scores 1from sklearn.metrics import roc_curve, auc
2import matplotlib.pyplot as plt
34def generate_auc_plot(labels, scores, title='Receiver operating characteristic', merge=True, figsize=(6,6), max_folds=10):
5""" Makes the nice fold-wise, average, and merged AUROC plots
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