Archives for machine learning underfitting
Whenever a data scientist works to predict or classify a problem, they first detect accuracy by using the trained model to the train set and then to the test set. If the accuracy is satisfactory, i.e., both the training and testing accuracy are good, then a particular model is considered for further development. But sometimes,…
The post Understanding Overfitting and Underfitting for Data Science appeared first on Analytics India Magazine.
While building a machine learning model, there is always the problem of underfitting and overfitting. Finding a sweet spot between these two requires diligent hyperparameter tuning. Researchers from top organisations and academia have been doing a lot in order to automate the hyperparameter tuning process. Some of the commercial offerings are Google AutoML, Amazon SageMaker,…
The post LG Introduces Auptimizer To Help Data Scientists Speed Up ML Model Tuning appeared first on Analytics India Magazine.
One of the major challenges in data science, especially concerning machine learning, is how well the models align themselves to the training data. Underfitting and overfitting are familiar terms while dealing with the problem mentioned above. For the uninitiated, in data science, overfitting simply means that the learning model is far too dependent on training…
The post Tackling Underfitting And Overfitting Problems In Data Science appeared first on Analytics India Magazine.