{"kind":"task","effective_mode":"full","benchmark":{"kind":"benchmark","effective_mode":"full","slug":"mmlu-pro","formal_name":"MMLU-Pro","introduction":"MMLU-Pro rebuilds MMLU with ten answer options instead of four and removes items that no longer separate models. Questions span fourteen academic and professional subjects.","introduction_ja":"","introduction_en":"","category":"Category not supplied","task_count":null,"acquisition_status":"Acquisition status not supplied","official_url":"https://huggingface.co/datasets/TIGER-Lab/MMLU-Pro","indexing_mode":"index","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[],"history":"","construction":"","limitations":"","saturation":"","scores":[]}},"task_id":"9314c2c9-ca4a-5d16-9759-a23b57eab907","task_key":"default--test--717","task_revision_id":"1","upstream_id":"717","short_description":"Suppose Q is a measure of output, K is a measure of capital stock in use, and L…","config":"default","split":"test","body":"{\"category\":\"business\",\"options\":\"['Polynomial regression', 'Linear progression', 'Quantile regression', 'Ridge regression', 'Logistic regression', 'Exponential regression', 'Lasso regression', 'Multiple regression', 'Single regression', 'Non-linear regression']\",\"question\":\"Suppose Q is a measure of output, K is a measure of capital stock in use, and L is a measure of the size of the employed labor force. Q =AK^\\\\betaL^\\\\gamma is a much used form of production function. When \\\\beta + \\\\gamma = 1, it is known as a Cobb-Douglas production function. This function has many convenient properties: Marginal products of both labor and capital are positive if \\\\beta and \\\\gamma are. If \\\\beta + \\\\gamma = 1, the function has constant returns to scale. That is, if both inputs are increased in like proportion, output will increase in that same proportion. A doubling of both inputs, for example, will result in doubled output. Discuss how the concept of linear regression might be applied to estimate \\\\beta and \\\\gamma .\",\"src\":\"stemez-Business\"}","display_format":"text","language":"","answer_status":"published","assets":[],"source_url":"https://huggingface.co/datasets/TIGER-Lab/MMLU-Pro","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}