New answers tagged machine-learning-model
1
vote
The accuracy of a random forest algorithm is nearly 1, how do I solve this problem? (with updates)
I guess the question is whether this is too good to be true, and if so what could be leading to it.
Domain knowledge is the first suggestion: if you know others have modeled this or similar problems, ...
- 12k
2
votes
The accuracy of a random forest algorithm is nearly 1, how do I solve this problem? (with updates)
To answer your questions: increasing the max depth of a Random Forest algorithm may increase complexity. Even though your 91% accuracy for the code you listed is test accuracy, this still could mean ...
- 151
0
votes
When should I do train test split and feature selection if my dataset is unbalanced?
Given Problem :-
This problem is about building a machine learning model to predict ECG signal quality from imbalanced data, where feature selection, data ...
0
votes
When should I do train test split and feature selection if my dataset is unbalanced?
Train/test split should be done before feature selection so that the selection of features for the model is independent of the test set (therefore, you can test the quality of the feature selection as ...
- 316
0
votes
How can I improve the precision of my regression model?
Few things you can do
Try with the Sequence models architectures
Remove stationarity from the time series if possible?
With current architectures, try adding more layers too.
- 31
0
votes
How can I improve the precision of my regression model?
The way you are drawing the points makes it look like you are dealing with a time series forecasting problem. If that is the case I would suggest changing from the feedforward NN architecture you are ...
- 26
0
votes
How can I improve the precision of my regression model?
have you tried feature scaling ? standardizing your features before training the model and try working with regularization techniques like l1,l2
try using different algorithms such as xgboost ...
1
vote
Is it possible for a feature not correlated with a dependent variable to become important in a machine learning model?
In the example above, the x1 and x2 features have extremely low correlation with the color variable, both being less than ...
- 4,044
1
vote
Is it possible for a feature not correlated with a dependent variable to become important in a machine learning model?
Yes. Perhaps the simplest examples have no linear relationship between the feature and target and hence zero correlation in the usual statistical sense, but have a clear nonlinear relationship (e.g. $...
- 12k
Top 50 recent answers are included