The KDD process is divided into three main steps: data preparation, data mining, and data interpretationAdrien CouletMalika SmaïlTabbonePascale BenlianAmedeo NapoliMarieDominique Devignes
Data preparation can be seen in the CRISP-DM model (though it can be reasonably argued that "data understanding" falls within our definition as well). We can also equate our data preparation with the framework of the KDD Process — specifically the first 3 major steps — which areselection,...
I have a nc file of 40 years for a variable recorded at daily temporal resolution. I would like to sum these over monthly intervals and have tried the following: cdo monsum inputfile.nc outputfile.nc Although this runs with no error, I only get one frame in the outpu...
The KDD (Knowledge Discovery in Databases) process has achieved excellent results in the classical database context and that is why we examine the possibility of adapting it to the Big Data context to take advantage of its strong and effective data processing techniques. We introduce therefore a ...
The Knowledge Discovery in Databases (KDD) process can involve a significant iteration and may contain loops among data selection, data preprocessing, data transformation, data mining, and interpretation of mined patterns. The most complex steps in this process are data preprocessing and data ...
Polymers with at least two stable and reversibly interchangeable oxidation steps, process for their preparation and their usePolymers which have two or more stable, reversibly interconvertible oxidation states with half-wave potentials E1/2of from -1.5 to +1 V, and which are obtained when a ...
POLYMERS WITH AT LEAST TWO STABLE AND REVERSIBLY INTERCHANGEABLE OXIDATION STEPS, PROCESS FOR THEIR PREPARATION AND THEIR USEPolymers which have two or more stable, reversibly interconvertible oxidation states with half-wave potentials E1/2of from -1.5 to +1 V, and which are obtained when a ...