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## ESIP Member Organization
CSISS/LAITS, George Mason University
Alaska Ocean Observing System (AOOS) and Axiom Data Science
## Mentors
Ziheng Sun
Jesse Lopez
## Project Ideas
Ag-Net: building …
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**分类**模型的话，训练数据分布很不均匀的时候，预测结果会有很大影响
多谢多谢
In classification model, when the train data is imbalance, the classification model do not work.
In this **ranking** model, for example:
all label : …
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Hi
First of all, let me thank you guys for your hardwork to make the xgboost available to us. it's such a great tool!
I am using xgboost in R. I came across a binary classification problem with a s…
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I am attempting to train model on AVA myself and faced very low quality of predictions. Digging further, I found predictions to be very strange and started to investigate pretrained models and asking …
hcl14 updated
5 years ago
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**Describe the solution you'd like**
For imbalanced classification problems it would be wonderful to have a precision recall plot. This would make a nice companion to ROC/AUC plots.
http://scikit-…
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Hi John,
Great work. I am also trying to reproduce the results from the chexnet paper for learning purposes. I just have 2 quick questions:
1. Did you modify the loss function to account for the…
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#### Description
Seems like `joblib` throws a warning regarding `cachedir`.
#### Steps/Code to Reproduce
Run the example [`plot_pipeline_classification.py`](https://github.com/scikit-learn-con…
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I am working with an imbalanced binary class data set for classification, with ~90% negative examples and ~10% positive examples and a batch size of 20 when training.
I am interested in ensuring, t…
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Hello and thank you for this project.
I am new to machine learning and have a little bit of trouble getting started with this.
If i got it correctly this method is used, when I have unevenly dis…