What's Hot - University of California, San Diego - UCSD
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VIEW POST By: geed
Lambda self rank ...Read More
By: geed
Posted: Oct 26, 2023 5:44:44 PM
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VIEW POST By: Lies lies
Pike Snu Fiji Aepi Tke Sigep Lambda Phidelt Beta Sammy Pikap p Triangle ...Read More
By: Lies lies
Posted: Oct 26, 2023 5:35:54 PM
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VIEW THREAD frat rankings updated By: dawg
frat rankings have hella changed recently so here is how it’s looking with fall quarter so far. why are 90%...Read More
By: dawg
Posted: Oct 26, 2023 5:22:55 PM
VIEW POST By: Lol
Undoubtedly another lambda self rank 😂 ...Read More
By: Lol
Posted: Oct 26, 2023 12:36:59 PM
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VIEW POST By: Ohmagawdbruhawhellnahman
Ohmygawdbruhawwhellnahmanwtfmangetyoah Ahh comment bruh lambda below sig ep they dont let the geed gates flood this year straight booty ahh class...Read More
By: Ohmagawdbruhawhellnahman
Posted: Oct 26, 2023 4:53:53 AM
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VIEW POST By: A
VIEW THREAD Updated unbiased Pre-Halloweekend Top Greek Life Rank By: Student
Lambda Pike Fiji / Snu AEPi/ Sig Ep Sammy Beta Pi Kapp Sammy Triangle (TKE not ranked due to SA allegations) ...Read More
By: Student
Posted: Oct 26, 2023 3:31:25 AM
VIEW POST By: stupid
someone in lambda wrote this...Read More
By: stupid
Posted: Oct 25, 2023 2:31:59 PM
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VIEW POST By: bro
it’s who they most associate with retard...Read More
By: bro
Posted: Oct 25, 2023 2:24:20 PM
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Didn't find your school?Request for your school to be featured on GreekRank.
By: SebastianPosted:
Model Comparison: Pseudo � 2 R 2 can be useful for comparing different logistic regression models on the same dataset. A higher pseudo � 2 R 2 usually indicates a better fit. Assessing Improvement: When you add or remove predictors from the model, pseudo � 2 R 2 can help you assess whether the model's fit has improved. Not for Explained Variance: It should not be used as a measure of the proportion of variance explained by the model, as it doesn't have the same interpretation as � 2 R 2 in linear regression. Not for Isolated Interpretation: Pseudo � 2 R 2 values are generally not useful for interpreting the quality of a model in isolation. They are more useful when comparing different models for the same dataset.
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