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The best algorithm(s) for finding the best hyperparameters (special case)

It seems as if you have tried the main tabular machine learning model types but I would suggest you to look into Optuna. It's a model-agnostic hyperparameter optimization framework which is awesome ...
Guest's user avatar
  • 1
-1 votes

I got 100% accuracy on my test set,is there something wrong?

decision_tree = DecisionTreeClassifier(max_depth=45) if we reduce the max depth .the issue can be solved
Sayali Jadhao's user avatar
2 votes

How to explain missing dates to a model?

I am not sure how you could define such a predictive model using Nixtla (I am unfamiliar with this software). However, tensorflow has a way you can mask specific timestamps. Perhaps this is what you'...
healthydata's user avatar
1 vote

How to measure different models' feature importance using a generic and common standard?

Permutation importance is a relatively simply model-agnostic approach. You train and score a model the usual way to get a reference score. Then you take each feature in turn, and score the model after ...
MuhammedYunus's user avatar
1 vote

Fitting users' reports with joint time-semantic model

What about using a Bayesian Classifier? https://en.wikipedia.org/wiki/Naive_Bayes_classifier#Examples Define as many features as you need. I mean, inner definitions of the data you want to study: ...
Alfred's user avatar
  • 11
0 votes

Random Forest plot standardized

I agree with lpounng's answer that the easiest thing to do it refit without having scaled. If for some reason that's not possible, you can modify the DOT code produced by sklearn, using the scaler's <...
Ben Reiniger's user avatar
  • 11.9k
2 votes
Accepted

What type of machine learning am I looking for with these column types?

Before struggling on 'what machine learning model to use', let's take a step back and ask 'does my features have a causal connection with the target?' Machine learning is no magic. It cannot predict ...
lpounng's user avatar
  • 1,075

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