How does Maximo Visual Inspection support data scientists in improving model accuracy after the model is trained?
Added by Andrew S.
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Adi S.
The goal in predictive analysis is to use training data to learn a model that can make predictions on new data. Answer the following questions. a. Suppose we increased the size of the training set. Would this likely improve or deteriorate the performance of the model on new data? Why? Increasing the size of the training set is likely to improve the model's performance on new data. Increasing the size of the training set tends to add more variability to the data. More variability tends to make it easier to detect which features are truly correlated with the target class and which features are not. b) Suppose we reduced the feature representation to include only the features with the highest mutual information with the target concept. Would this likely improve or deteriorate the performance of the model on new data? Why?
Sri K.
Bao is reviewing a diagnostic AI model when he notices something strange. The data set is larger than it should be. After reviewing the activity over the past weeks, he notices that extra items were placed in the data set that could have resulted in the AI model rendering incorrect diagnoses. However, the AI model was able to process the bogus data and still render accurate and correct diagnoses for each data item. This is an example of which of the following? Fluency Robustness Fidelity Fairness
Lien L.
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