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IcannotFixThis
  • Member for 10 years, 9 months
  • Last seen more than a month ago
10 votes
Accepted

Gradient boosting - extreme predictions vs predictions close to 0.5

10 votes

When is unbalanced data really a problem in Machine Learning?

7 votes
Accepted

Why gradient boosting/random forest generate "unstable" feature importance?

6 votes

standardising non normally distributed predictors for regression

4 votes

Surveys: Is 25% of a large user base representative?

4 votes
Accepted

Residuals in a Machine Learning with forecasting

3 votes

Is autocorrelation in a supervised learning dataset a problem?

3 votes

Outlier removal before Boosted Decision Tree Regression

3 votes

Bayesian time series - more weight on recent observations?

3 votes

Cross-correlation between two seasonal series

2 votes

Features, samples, and over-fitting?

2 votes
Accepted

quantile estimation issue

2 votes

Making sense out of the standard error formula

2 votes

Why is the restricted boltzmann machine both unsupervised and generative?

2 votes

Estimates of multiple linear regression parameters

2 votes
Accepted

PCA on prices or returns

2 votes
Accepted

Correlation matrix and redundant information

2 votes

Cross validation in ExtraTreesRegressor

2 votes

clarification on k fold cross validation

2 votes

Data scientist interview question: Linear regression low $R^2$ and what would you do

1 vote

Handle missing value in continuous variable in Decision Tree without losing its meaning

1 vote

Neural-Network- Training and Testing; Validation performance analysis

1 vote

Neural Network Optimization Algorithms

1 vote

Back propagation and and various cost functions

1 vote

Why is convolution operation an integral?

1 vote

data normalization after dimension reduction for classification

1 vote

Fit a curve to a probability distribution

1 vote

Is it possible to generate data for stochastic process with specific distribution and autocorrelation?

1 vote

Antisymmetric components in Gaussian kernel

0 votes

Grouping 1D data to find intervals with most data points