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Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.

8 votes
4 answers
6k views

How does PCA behave when there is no correlation in the dataset?

We all know that Principal Component Analysis is executed on a Covariance/Correlation matrix, but what if we have a very high dimensional data, assuming 75 features and 157849 rows? How does PCA tackl …
Atul Mishra's user avatar
2 votes
1 answer
272 views

LGBM Intuition to Non-technical individuals

How can i explain LGBM to a non-technical person as it involves Trees/Ensembling and much more? Using LGBM for solving a Regression problem and how does it helps in: Better Prediction Feature Import …
Atul Mishra's user avatar
1 vote

Cross-validation for (hyper)parameter tuning to be performed in validation set or training set?

I believe you are looking for a hard-rule stating how the data should be distributed. Well it is totally your call. Approach 1 is most widely used, but a better split would be 50% for training, 30% fo …
Atul Mishra's user avatar
0 votes
1 answer
38 views

Statistical/Automated method for identifying a dataset suitable for Machine Learning Modelling

Given a folder which has 10k Excel files, the objective is to identify the datasets suitable for Machine Learning Modelling Approach. We use a script right now which performs this operation and call i …
Atul Mishra's user avatar
0 votes
Accepted

Statistical/Automated method for identifying a dataset suitable for Machine Learning Modelling

The Major, criteria i was looking for any Modular changes/multiple oscillations to track. Explored few methods like Stationarity Test and Interdaily Stability, but both of these methods have assumptio …
Atul Mishra's user avatar