Author: Dr. Niraj Kumar

Winning Ensemble Classification Strategies

With the increase in the complexity of data, and to fulfill the accuracy-related requirements, people started preferring ensemble classifiers. However, the selection of ensemble classifiers is not that easy. We have a lot of ensemble strategies, like: (1) Model Averaging, (2) Weighted Model Averaging, (3) Majority Voting, (4) Bagging, (5) Boosting, (6) Stacking, (7) Blending,

Continue reading

How to use LSTM with 1D, 2D and 3D Array?

Actually LSTM supports three-dimensional input. They are – (samples, time steps, features) Samples. One complete sequence is considered as one sample. A batch may contains one or more samples. In NLP, if we are dealing with the text at sentence level (means taking one sentence at a time), then our sample size will be one.

Continue reading

Multi-Tasking Deep Learning

We can divide the Multi-task learning into four layers. Here Shared layer learns jointly learns important features from text input and plays a very important role. Finally, Task-Layer uses this jointly learned features for different task specific predictions. However, in complex Multi-Task learning, the Task layer can use additional features (additional to that learned from

Continue reading