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... The NDVI is computed from the ratio of red and infrared reflectance. NIR and RED are the amounts of near-‐infrared and red light, respectively, reflected by the vegetation and captured by the ...
... The NDVI is computed from the ratio of red and infrared reflectance. NIR and RED are the amounts of near-‐infrared and red light, respectively, reflected by the vegetation and captured by the ...
The Power of the Group Processing Facility in SAS® Enterprise Miner
... define group variables such as GENDER or JOB, in order to obtain separate analyses for each level of the group variable or variables. use cross validation techniques to test the stability of predictive models specify index looping, or how many times the flow following the node should loop resample t ...
... define group variables such as GENDER or JOB, in order to obtain separate analyses for each level of the group variable or variables. use cross validation techniques to test the stability of predictive models specify index looping, or how many times the flow following the node should loop resample t ...
What is Data Warehouse?
... data that measures the organizations business operations. A fact table might contain business sales events such as cash register transactions or the contributions and expenditures of a nonprofit organization. Fact tables usually contain large numbers of rows, sometimes in the hundreds of millions of ...
... data that measures the organizations business operations. A fact table might contain business sales events such as cash register transactions or the contributions and expenditures of a nonprofit organization. Fact tables usually contain large numbers of rows, sometimes in the hundreds of millions of ...
Data Miing and Knowledge Discvoery - Web
... 1. Divide the available data into a training set and an evaluation set 2. Split the training data into n folds 3. Select an algorithm and training parameters 4. Train and test n models using the n train-test splits 5. Repeat step 2 to 4 using different algorithms / parameters and compare m ...
... 1. Divide the available data into a training set and an evaluation set 2. Split the training data into n folds 3. Select an algorithm and training parameters 4. Train and test n models using the n train-test splits 5. Repeat step 2 to 4 using different algorithms / parameters and compare m ...
Module 6 Statistics Review
... Discrete variable distribution Probability of event occurrence Models ...
... Discrete variable distribution Probability of event occurrence Models ...
Statistics and Error and Data Analysis for Particle and Nuclear Physics
... The goal of this scenario is to introduce the students to the fact that detectors have large inefficiencies, which must be taken into account while analysing the data. The scenario focuses on a rather simple approach that relies on Monte Carlo for evaluating the correction factor. The cos2ș observab ...
... The goal of this scenario is to introduce the students to the fact that detectors have large inefficiencies, which must be taken into account while analysing the data. The scenario focuses on a rather simple approach that relies on Monte Carlo for evaluating the correction factor. The cos2ș observab ...
