{ "name": "Diamonds", "source": "https://www.kaggle.com/datasets/shivam2503/diamonds/data", "data_intro": "This classic dataset contains the prices and other attributes of almost 54,000 diamonds. Try to analyze diamonds by their cut, color, clarity, price, ", "is_splited": false, "overall_size": 53940, "train_size": 0, "test_size": 0, "c_classes": 3, "n_classes": 8, "task_type": "regression", "target": { "price": "Given a diamond's cut,color,clarity and other attributes, predict its price in US dollars" }, "cat_feature_intro": { "cut": "- cut: Describe cut quality of the diamond. Fair(worst), Good, Very Good, Premium, Ideal(best)", "color": "- color: Color of the diamond, J(worst), I, H, G, F, E, D(best)", "clarity": "- clarity: a measurement of how clear the diamond is ,I1 (worst), SI2, SI1, VS2, VS1, VVS2, VVS1, IF (best))" }, "num_feature_intro": { "#": "- #: index counter", "carat": "- carat: Carat weight of the diamond (0.2--5.01)", "depth": "- depth: total depth percentage = z / mean(x, y) = 2 * z / (x + y) ", "table": "- table: width of top of diamond relative to widest point", "price": "- price: the price of the diamond in US dollars", "x": "- x: length in mm ", "y": "- y: width in mm ", "z": "- z: depth in mm " }, "evaluation_metric": null, "num_feature_value": { "#": [], "carat": [ 0.2, 5.01 ], "depth": [ 43.0, 79.0 ], "price": [ 326.0, 18823.0 ], "table": [ 43.0, 95.0 ], "x": [ 0.0, 10.74 ], "y": [ 0.0, 58.9 ], "z": [ 0.0, 31.8 ] }, "cat_feature_value": { "clarity": [ "I1", "IF", "SI1", "SI2", "VS1", "VS2", "VVS1", "VVS2" ], "color": [ "D", "E", "F", "G", "H", "I", "J" ], "cut": [ "Fair", "Good", "Ideal", "Premium", "Very Good" ] } }