{"blocks": [{"key": "5a58d521", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "a1931df3", "text": "On-site ML case – income bracket missing in California housing data", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "905e01d5", "text": "Question", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "8df1d28f", "text": "Training data lack the lowest-income bracket (<$25 k). Build a model that will still perform well across all income ranges, including the unseen bracket.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "763118b4", "text": "Hints", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "baac6792", "text": "Use domain similarity, incremental retraining, covariate shift correction, transfer learning, feature scaling.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}