Ensembling
Week- 4 Ensembling >>> How to Win a Data Science Competition: Learn from Top Kagglers
Programming Assignment: Ensembling implementation
Select the true statements about the validation schemes.
Select fair validation schemes. The definition for the schemes can be found in the reading material.
Still, sometimes it is beneficial to tune \alphaα and betabeta independently, e.g. mix with \alpha=0.1α=0.1 and \beta=0.8β=0.8 works best.
However, for some metrics it never makes sense to tune \alphaα and \betaβ independently. That is, searching for independent \alphaα and \betaβ will never give you better results than searching for weights, constrained to be \beta = 1 – \alphaβ=1−α. Select such metrics.
Week – 2 Validation >>> How to Win a Data Science Competition: Learn from Top Kagglers 1. Select true statements 1 point Performance increase on a fixed cross-validation split guaranties…
Week – 3 Mean encodings >>> How to Win a Data Science Competition: Learn from Top Kagglers 1. What can be an indicator of usefulness of mean encodings? 1 point…
Week – 4 Graded Advanced Features II Quiz >>> How to Win a Data Science Competition Learn from Top Kagglers 1. Imagine that we apply X = PCA(n_components=5).fit_transform(data) and data…
Week – 1 Recap of How to Win a Data Science Competition 1. What back propagation is usually used for in neural networks? 1 point To propagate signal through network…
Week – 1 Feature extraction from text and images >>> How to Win a Data Science Competition: Learn from Top Kagglers 1. Select true statements about n-grams 2 points N-grams…
Week – 1 Graded Soft/Hard Quiz of How to Win a Data Science Competition Learn from Top Kagglers 1. Which library provides the most convenient way to perform matrix multiplication?…