Row 65960

Row ID: 65960 | Dataset Entry | Axioma AXP Content Repository

Content Data

This page contains data entry 65960 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

Yes, but they come out to the same thing in the predictive posterior (where you, as you say, marginalize over the posterior)

p\_klqp(x\_test | X\_train) = int p(x\_test | z)q\_klqp(z | X\_train) dz

would underestimate predictive variance, while

p\_klpq(x\_test | X\_train) = int p(x\_test | z)q\_klpq(z | X\_train) dz

could overestimate it.

FieldValue
text Yes, but they come out to the same thing in the predictive posterior (where you, as you say, marginalize over the posterior) p\_klqp(x\_test | X\_train) = int p(x\_test | z)q\_klqp(z | X\_train) dz would underestimate predictive variance, while p\_klpq(x\_test | X\_train) = int p(x\_test | z)q\_klpq(z | X\_train) dz could overestimate it.
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-23
username_encoded Z0FBQUFBQm5Lak1jdW5wZkVNRk12aElYekJ2dUUyRlZzbEprLXFJXzNxYzFPQS1yeVcxLWF0cUpWS3RzYkZkU2JLYnZsa2t5dW4tTGNsQUxiV2ZKQ2I1VDB5WkhaX0Rkc1E9PQ==
url_encoded Z0FBQUFBQm5Lak9zX1lxUTZ6d1VXRU9RZHcyM3RFSGlEY04wX2VJNEUycUR2UnpITl90TnQyZ0ZPdmlJZk9rMzF1UTZIMHFCb213UW5qcG1Tc002XzBjaUFhbGhTcEdNaGxiVWEwaVpEQVpVMXhyZFhNVk40dmxWaTBWcGtRVTJfVkIwNnhLSFpmZ285LVZ1WmltWlJOakV1X0RuZlhNX3A1d3RmY2VIbHpsXzFhRkZiZ2Y3N01xeVRIdUZjZEtuR1JxWC1xRkNaQXNXamVub2xTdXRMblU0a0pJVDlFaWJkSjBKc1FNcEE2Zk9pTHQ4N1E0YnhfZz0=

Raw Record

{
  "text": "Yes, but they come out to the same thing in the predictive posterior (where you, as you say, marginalize over the posterior)\n\np\\_klqp(x\\_test | X\\_train) = int p(x\\_test | z)q\\_klqp(z | X\\_train) dz\n\nwould underestimate predictive variance, while\n\np\\_klpq(x\\_test | X\\_train) = int p(x\\_test | z)q\\_klpq(z | X\\_train) dz\n\ncould overestimate it.",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-23",
  "username_encoded": "Z0FBQUFBQm5Lak1jdW5wZkVNRk12aElYekJ2dUUyRlZzbEprLXFJXzNxYzFPQS1yeVcxLWF0cUpWS3RzYkZkU2JLYnZsa2t5dW4tTGNsQUxiV2ZKQ2I1VDB5WkhaX0Rkc1E9PQ==",
  "url_encoded": "Z0FBQUFBQm5Lak9zX1lxUTZ6d1VXRU9RZHcyM3RFSGlEY04wX2VJNEUycUR2UnpITl90TnQyZ0ZPdmlJZk9rMzF1UTZIMHFCb213UW5qcG1Tc002XzBjaUFhbGhTcEdNaGxiVWEwaVpEQVpVMXhyZFhNVk40dmxWaTBWcGtRVTJfVkIwNnhLSFpmZ285LVZ1WmltWlJOakV1X0RuZlhNX3A1d3RmY2VIbHpsXzFhRkZiZ2Y3N01xeVRIdUZjZEtuR1JxWC1xRkNaQXNXamVub2xTdXRMblU0a0pJVDlFaWJkSjBKc1FNcEE2Zk9pTHQ4N1E0YnhfZz0="
}
Explore Dataset Explore Row

Entry Information