Mehta, M., Agrawal, R., & Rissanen, J. (1996). SLIQ: A fast scalable classifier for data mining. In Extending Database Technology (p. 18-32). Avignon, France: Springer. Home/Search Document Details and Download
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....and born in Canada, with the attributes birth place and address in consideration. find classification rules for cs students according to gpa related to birth place, address This query will first collect the relevant set of data, and then execute some data classification algorithm, such as [14, 21] to classify students according to their gpa s and present each class and its associated characteristics. Mining association rules. Query (q4) is to find strong association relationships for those students majoring in computing science and born in Canada, in relevance to the attributes gpa, ....
M. Mehta, R. Agrawal, and J. Rissanen. SLIQ: A fast scalable classifier for data mining. In Proc. 1996.
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.... shown that larger training sets (typically involving several million records) improve accuracy of the classification model [12, 13] It means that decision trees built by an approximate approach can carry a significant loss of accuracy in comparison with trees built by an exact approach like SLIQ[7] and SPRINT[17] The CLOUDS algorithm Instead of computing gini index for each distinct value of a numeric attribute, the CLOUDS algorithm samples the splitting points followed by an estimation step to narrow the search space of the best split. In CLOUDS, the range of each numeric attribute is ....
....second split second split 1 3 4 2 3 4 Figure 6. Splitting Matrices Twice into 4 Sub nodes [1] For each attribute i do [2] If (i is the X axis or Y axis of submatrix) then [3] gini = gini index on the submatrix along X or Y axis [5] gini = gini Index on attribute i of the parent node [7] End For [8] Return the attribute having the minimal gini Index Figure 7. predictSplit(node,submatrix) However, if the first splitting attribute is on any of the Yaxis, we won t be able to split the subnodes again without a data scan since we do not have the histogram of attributes on the rest ....
M. Mehta, R. Agrawal, and J. Rissanen. "SLIQ: A Fast Scalable Classifier for Data Mining." Proc. of Fifth Int'l Conference on Extending Database Technology, pages 18-32, March 1996.
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M. Mehta, R. Agrawal, and J. Rissanen, "SLIQ: A Fast Scalable Classifier for Data Mining," Proc. Fifth Int'l Conf. Extending Database Technology, 1996.
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Mehta, M., Agrawal, R., & Rissanen, J. (1996). SLIQ: A fast scalable classifier for data mining. In Extending Database Technology (p. 18-32). Avignon, France: Springer.
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Mehta, M., Agrawal, R., & Rissanen, J. (1996). SLIQ: A fast scalable classifier for data mining. In Extending Database Technology (p. 18-32). Avignon, France: Springer.
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