CodeX
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CodeX

How to handle missing environmental data

They reviewed a bunch of imputation techniques to find the best

The datasets used. Note the use of all 3 attribute types.

The Positives

Defining the Problem + Constraints Clearly

“Organizing environmental data in well-structured databases is a challenging task (Blair et al., 2019). On the one hand, the natural environment is impacted by human activities, and this calls for interdisciplinary research and analysis. On the other hand, natural phenomena cover different time and spatial scales and are generally interconnected, which makes data integration difficult. This typically results in heterogeneous data sources and generally gives rise to databases of a mixed nature, with both qualitative and quantitative entries.”

Accounting for Variance

A good representation

Looking at Performance

Straight outta the abstract

Qualitative Datasets

Quantitative Datasets

Mixed Data

A note on Processing Times

Closing

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Devansh- Machine Learning Made Simple

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