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import pandas as pd
from matplotlib import pyplot as plt
import numpy as np
df = pd.read_csv(r"C:\Users\mdmar\Downloads\Thesis\Data/1024.csv")
#print(df.head())
#sizes = df['target'].value_counts…
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# CrossValidation 交叉验证
## Reference
- [几种交叉验证(cross validation)方式的比较](https://www.cnblogs.com/ysugyl/p/8707887.html)
- [sklearn - cross validation](https://scikit-learn.org/stable/modules/cro…
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What is the recommended way to do K-fold cross validation with a webdataset? I wasn't able to find any examples on it.
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In Chapter2, we had make a training set by using stratified sampling to guarantee that the test set is representative of the overall population. However, in the "Better Evaluation Using Cross-Validat…
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When considering incremental models how much do we care about k-fold cross validation? My understanding is that the k-fold bit is an effort to train on all of our data, while still protecting testing…
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○ Time: 6 weeks
○ Tools Required: Scikit-learn, TensorFlow, PyTorch (within Azure AI Studio or Microsoft Fabric)
○ Steps:
1. Define model requirements and objectives.
□ Utilize histor…
zepor updated
1 month ago
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This code (k-fold cross val) misses a parenthesis on np.concatenate:
'''k = 3
num_validation_samples = len(data) // k
np.random.shuffle(data)
validation_scores = []
for fold in range(k):
…
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- [x] k-fold-cross-validation
- [ ] leave-one-out cross validation
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These approaches are often used in financial ML. Can benefit a wide variety of ML tasks though.
In short: Adding a safety gap between the k-folds or train-, test- and validation splits.
These ar…