Cisco Interview Question | Dimension Reduction
Question
You are given a train data set having 1000 rows and 1 Million columns. The data set is based on a classification problem. You are asked to reduce the dimension of this data so that model computation time can become manageable. What will be your suggestion?
(You are free to make practical assumptions.)
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Answer ( 1 )
There are various ways to reduce dimensions:
1. Use L1 or lasso regression where the non-important parameters will be eliminated
2. Use Principal Component analysis
3. Use t-SNE(t-distributed stochastic neighbour embedding)