Details
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Bug
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Status: Open
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Major
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Resolution: Unresolved
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None
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None
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None
Description
These problems may be just numerical issues with too large the condition numbers or too small of a training set. To be investigated.
> PivotalR:::test(filter="glm") Running tests ------------------------- Test cases for madlib.glm and its helper functions : .port? 5431 .dbname? madlib-pg93 .................... WARNING: GLM warning: the computation did not converge in 20 iterations! CONTEXT: PL/Python function "glm" 1.2................. WARNING: GLM warning: the computation did not converge in 20 iterations! CONTEXT: PL/Python function "glm" .... WARNING: Hessian or gradient is not finite. CONTEXT: SQL statement " SELECT __madlib_temp_75741577_1437438071_4375895__ AS __madlib_temp_75741577_1437438071_4375895__, sex , 4 AS __madlib_temp_48749745_1437438071_22969480__, ( madlib.__glm_binomial_probit_agg( ((("rings") < (10))::integer)::double precision, (array[1,"length","diameter","height","whole","shucked","viscera","shell"])::double precision[], __madlib_temp_43345218_1437438071_11277539__.__madlib_temp_69537766_1437438071_32811656__) ) AS __madlib_temp_69537766_1437438071_32811656__ FROM ( SELECT *, array_to_string(ARRAY[sex::text], ',' ) AS __madlib_temp_75741577_1437438071_4375895__ FROM "pg_temp_3"."madlib_temp_d763e98a_0753_969a95_03cedf5694ab" ) AS _src JOIN ( SELECT unnest($1) AS __madlib_temp_75741577_1437438071_4375895__, unnest($2) AS __madlib_temp_69537766_1437438071_32811656__ ) AS __madlib_temp_43345218_1437438071_11277539__ USING (__madlib_temp_75741577_1437438071_4375895__) GROUP BY sex, __madlib_temp_75741577_1437438071_4375895__ " PL/Python function "glm" WARNING: Hessian or gradient is not finite. CONTEXT: SQL statement " SELECT __madlib_temp_75741577_1437438071_4375895__ AS __madlib_temp_75741577_1437438071_4375895__, sex , 5 AS __madlib_temp_48749745_1437438071_22969480__, ( madlib.__glm_binomial_probit_agg( ((("rings") < (10))::integer)::double precision, (array[1,"length","diameter","height","whole","shucked","viscera","shell"])::double precision[], __madlib_temp_43345218_1437438071_11277539__.__madlib_temp_69537766_1437438071_32811656__) ) AS __madlib_temp_69537766_1437438071_32811656__ FROM ( SELECT *, array_to_string(ARRAY[sex::text], ',' ) AS __madlib_temp_75741577_1437438071_4375895__ FROM "pg_temp_3"."madlib_temp_d763e98a_0753_969a95_03cedf5694ab" ) AS _src JOIN ( SELECT unnest($1) AS __madlib_temp_75741577_1437438071_4375895__, unnest($2) AS __madlib_temp_69537766_1437438071_32811656__ ) AS __madlib_temp_43345218_1437438071_11277539__ USING (__madlib_temp_75741577_1437438071_4375895__) GROUP BY sex, __madlib_temp_75741577_1437438071_4375895__ " PL/Python function "glm" 34..............5.......................... 1. Failure (at test-madlib_glm.r#78): Test gaussian(inverse) ------------------------------------------ fit.db$coef not equal to fit.r$coefficients[, 1] 8/8 mismatches (average diff: 0.00719). First 8: pos x y diff 1 0.1970 0.1990 -0.00196 2 -0.0243 -0.0254 0.00112 3 -0.1709 -0.1630 -0.00793 4 -0.2059 -0.2462 0.04027 5 -0.0476 -0.0465 -0.00112 6 0.1413 0.1397 0.00156 7 0.0564 0.0577 -0.00130 8 -0.0146 -0.0123 -0.00222 2. Failure (at test-madlib_glm.r#86): Test gaussian(inverse) with categorical features ---------------- fit.db$coef not equal to fit.r$coefficients[, 1] 10/10 mismatches (average diff: 0.00517). First 10: pos x y diff 1 0.18215 0.18410 -1.94e-03 2 0.01223 0.01214 8.72e-05 3 -0.00158 -0.00153 -4.83e-05 4 -0.02981 -0.03107 1.26e-03 5 -0.13631 -0.12955 -6.76e-03 6 -0.19904 -0.23515 3.61e-02 7 -0.04775 -0.04668 -1.07e-03 8 0.14030 0.13905 1.26e-03 9 0.06185 0.06311 -1.26e-03 10 -0.01741 -0.01550 -1.91e-03 3. Failure (at test-madlib_glm.r#154): Test binomial(probit) with grouping ---------------------------- fit.db[[1]]$coef not equal to fit.r[[1]]$coefficients[, 1] 8/8 mismatches (average diff: 3.43). First 8: pos x y diff 1 2.79 1.73 1.063 2 5.41 5.73 -0.317 3 -3.23 -1.48 -1.742 4 -12.52 -9.37 -3.157 5 -16.51 -11.62 -4.893 6 21.90 16.00 5.899 7 13.38 7.96 5.423 8 2.33 -2.62 4.957 4. Failure (at test-madlib_glm.r#155): Test binomial(probit) with grouping ---------------------------- fit.db[[1]]$std_err not equal to fit.r[[1]]$coefficients[, 2] 8/8 mismatches (average diff: Inf). First 8: pos x y diff 1 0.582 Inf -Inf 2 2.559 Inf -Inf 3 3.334 Inf -Inf 4 4.176 Inf -Inf 5 2.934 Inf -Inf 6 3.257 Inf -Inf 7 3.928 Inf -Inf 8 3.629 Inf -Inf 5. Failure (at test-madlib_glm.r#214): Test poisson(identity) with grouping --------------------------- fit.db[[1]]$coef not equal to fit.r[[1]]$coefficients[, 1] 8/8 mismatches (average diff: 0.13). First 8: pos x y diff 1 2.74 2.75 -0.00483 2 -1.76 -1.78 0.02177 3 5.83 5.81 0.02412 4 27.36 27.45 -0.08863 5 2.67 2.44 0.22605 6 -7.71 -7.38 -0.32432 7 -5.89 -5.72 -0.16966 8 14.88 15.06 -0.17732 Error: Test failures In addition: Warning messages: 1: glm.fit: algorithm did not converge 2: glm.fit: algorithm did not converge 3: glm.fit: algorithm did not converge 4: glm.fit: fitted probabilities numerically 0 or 1 occurred 5: glm.fit: algorithm did not converge 6: glm.fit: fitted probabilities numerically 0 or 1 occurred
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