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·85d·Pinned# announcements
Snorkel now supports latest PyTorch release 1.4.0
We've upgraded our dependencies to support torch>=1.2.0, which includes the latest stable version, 1.4.0. These changes are available in our latest release, snorkel==0.9.5. We're excited to see what you build with Snorkel and the latest deep learning libraries!
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questions on snorkel-metal example
I am trying to use snorkel-metal for a hierarchical labeling problem (https://github.com/HazyResearch/metal/blob/master/tutorials/Multitask.ipynb ). I have a few questions on the parameters that need to be passed: 1. There are three tasks and overall 6 labels. The label matrices…
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How can we observe last entry in Σ(doubt in June 2019 workshop slides)
https://www.dropbox.com/sh/ipxmm6twu4p2qo1/AACztdxm-GTWxOkA7PfX2ooaa/Day%201?dl=0&preview=04_Theory_Apps.pdf&subfolder_nav_tracking=1 In the slides mentioned here, on the slide "Solution Sketch: Using the covariance ", it is given that we can observe the last cell(bottom right)…
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noise aware loss function for categorical cross entropy
For the discriminative model, the snorkel paper suggest using a noise aware loss function. I was going through this tutorial https://www.snorkel.org/use-cases/01-spam-tutorial which suggests working directly sklearns classifiers. 1. I guess it is okay to use default loss…
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Snorkel source code that uses dependency graphs?
The current snorkel source code's label model does not seem to use the created c_tree in calculating the final labels and associated probabilities : https://github.com/snorkel-team/snorkel/blob/master/snorkel/labeling/model/label_model.py Would it be possible for you to release…
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application of Snorkel to remote sensing data
Hi everyone, Can someone point me to any examples of using Snorkel for a remote sensing application? Our team is considering testing it in high-res satellite imagery (1m) to segmenting streams. Thank you!
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snorkel labeling pipeline steps in production
Snorkel does weak supervised learning. Suppose i have a label model and discriminative model trained on some data. I am wondering how a snorkel based labeling pipeline that runs daily looklike. Are there any downsides to doing fit on the fresh batch of data that comes…
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·27d# help
LabelModel conflicts with labeling function outputs
I have a binary classification problem with ~10 labeling functions. I am seeing records where nine lfs abstain (-1), one fires negative (0) (not the same lf every time), but once I fit and apply LabelModel, the predicted label is positive (1). I.e. I'm getting a positive label…
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Overlap vs conflict
Hi, Can anyone explain the difference between overlap and conflict with respect to labeling functions?
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