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Results tagged with python
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user 98127
Use for data science questions related to the programming language Python. Not intended for general coding questions (which should be asked on Stack Overflow).
1
vote
Accepted
Best parameters to try while hyperparameter tuning in Decision Trees
There are no combinations that work for all cases, hyperparameter tuning is still something that is mostly done by trial and error. Things like Gridsearch and Randomsearch exist though.
A good start i …
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3
votes
Accepted
Why Does XGBoost Keep One Feature at High Importance?
According to the docs "gain" is the default, which is calculated by this formula, where I don't think intuition would help. General consensus is, that feature importance is a tricky concept, as long a …
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0
votes
Error with pandas dataframe (needs to be 1-dimensional)
It seems to me that this question is better off on stackoverflow.
Nevertheless, X_cal gets generated from X_train and X_train from valid. But this is an atleast 2-dimensional dataframe with new_host a …
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0
votes
Looking for spatial clusters and anomalies. Is DBSCAN the right tool?
Check out this comparison here. Intuitively I would say fit on everything you've got, don't throw anything away.
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1
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Why is the accuracy of a LinearSVC not the same as the SDGClassifier?
When used with loss="hinge" The SGDClassifier gives a LinearSVM, so they should be the same. This is matter of choosing the same hyperparameters for both. Can you check that you using the exact same p …
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0
votes
Is it possible to get worse model after optimization?
This question is a little wrong-worded. You cannot get worse after optimization, otherwise it wouldn't be optimization! (At worst you are at the same performance like before, getting the exact same pa …
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1
vote
Accepted
What exactly is convergence rate referring to in machine learning?
A rate is always a gain per some time/step. A rate can exist even if the maximum is never reached. In supervised learning a loss function is defined, which is expected to have a global maximum, that w …
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1
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What does all zero mean decrease in accuracy (MDA/permutation importance) signify?
I am assuming MDA means Mean Decrease Accuracy. Generally speaking, a good performance on a validation/testing dataset means that your model generalizes well.
On the other hand MDAs of all exactly zer …
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1
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Binary classification: how to transform features in real numbers?
The term you are looking for is text classification. There exists a huge number of tutorials and papers out there, for example this tutorial and this survey.
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2
votes
Accepted
Why are the ANN training and validation accuracy graphs not smooth?
Considering that your validation accuracy has bigger steps than your training accuracy, this may simply be an issue of data size. Accuracy counts correct/not correct, so if the model switches its opin …
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