glm function crashing RStudio
1
I am trying to find the probability of a Swinging Strike on a various number of factors, including the count, Release Speed, Spin Rate. I have pitch by pitch data. I changed the value of Pitch Result to 0 and 1 (1 being a Swinging Strike, 0 being others). The dataset includes 380,000+ rows.
Data:
str(FastballData1)
'data.frame': 389035 obs. of 30 variables:
$ GameId : int 449257 449257 449257 449257 449257 449257 449257 449257 449257 447167 ...
$ HomeTeamId : int 108 108 108 108 108 108 108 108 108 108 ...
$ AwayTeamId : int 117 117 117 117 117 117 117 117 117 118 ...
$ Inning : int 1 1 5 1 1 2 1 2 5 4 ...
$ InningTop : int 0 0 0 0 0 0 0 0 0 0 ...
$ PlateAppearance : int 2 2 2 2 2 7 2 7 2 4 ...
$ PitchOfPA : int 4 6 1 1 2 4 3 3 3 1 ...
$ Balls : int 2 3 0 0 0 2 1 2 0 0 ...
$ Strikes : int 1 2 0 0 1 1 1 0 2 0 ...
$ PitchResult : num 0 0 0 0 0 0 0 0 0 0 ...
$ BatterId : int 77171 77171 77171 77171 77171 77171 77171 77171 77171 77171 ...
$ PitcherId : int 64271 64271 64271 64271 64271 64271 64271 64271 64271 31921 ...
$ CatcherId : int 59270 59270 59270 59270 59270 59270 59270 59270 59270 67658 ...
$ UmpireId : int 427248 427248 427248 427248 427248 427248 427248 427248 427248 427156 ...
$ BatSide : Factor w/ 2 levels "L","R": 2 2 2 2 2 2 2 2 2 2 ...
$ PitchHand : Factor w/ 2 levels "L","R": 2 2 2 2 2 2 2 2 2 2 ...
$ PitcherSet : Factor w/ 2 levels "Stretch","Windup": 2 2 1 2 2 1 2 1 1 1 ...
$ PitchType : Factor w/ 2 levels "Fastball","Slider": 1 1 1 1 1 1 1 1 1 1 ...
$ ReleaseSpeed : Factor w/ 163594 levels "100.003","100.004",..: 118138 113206 96757 105450 108863 104792 99623 88801 106163 118932 ...
$ PitchTimeToPlate : num 0.409 0.41 0.412 0.415 0.412 ...
$ SpinAxis : Factor w/ 176445 levels "-0.389885","-0.468337",..: 105104 92644 108361 90391 102961 103650 106045 109234 109359 123561 ...
$ SpinRate : Factor w/ 89264 levels "1002.54","1005.62",..: 51306 60703 54411 46083 47822 32355 50456 49402 47238 44709 ...
$ HorzBreakPFX : num -6.64 -4.49 -7.85 -4.33 -5.69 ...
$ VertBreakPFX : num 8.44 9.62 8.92 10.16 7.95 ...
$ ReleaseHeight : num 5.48 5.4 5.32 5.51 5.53 ...
$ ReleaseSide : num 2.11 2.03 1.82 1.96 2.02 ...
$ Extension : num 5.91 6.18 6.45 5.88 6.07 ...
$ VertApproachAngle: Factor w/ 319725 levels "-0.216948","-0.31733",..: 173138 100071 94338 93526 224459 83541 172155 116761 79538 90746 ...
$ HorzApproachAngle: Factor w/ 409250 levels "-0.0001026","-0.000107",..: 130394 205101 54294 165802 185810 128876 159926 91503 109419 78589 ...
$ bscount : chr "2-1" "3-2" "0-0" "0-0" ...
I am trying to run the following code:
glm(PitchResult ~ ReleaseSpeed + bscount + SpinRate,
data = FastballData1, family = binomial)
However, when I do this it shows this code resulting in 96 GB (which is ridiculous) thus causing R Studio to crash. My guess is it seems this creates a circular reference.
Does anyone have any suggestions on how to fix this? Or any other ways to best calculate the probability of a swinging strike based on the above factors?
r rstudio probability glm
edited Nov 24 '18 at 0:52
user20650
17.1k43468
asked Nov 24 '18 at 0:48
gracergracer
193
|
show 1 more comment
1
I am trying to find the probability of a Swinging Strike on a various number of factors, including the count, Release Speed, Spin Rate. I have pitch by pitch data. I changed the value of Pitch Result to 0 and 1 (1 being a Swinging Strike, 0 being others). The dataset includes 380,000+ rows.
Data:
str(FastballData1)
'data.frame': 389035 obs. of 30 variables:
$ GameId : int 449257 449257 449257 449257 449257 449257 449257 449257 449257 447167 ...
$ HomeTeamId : int 108 108 108 108 108 108 108 108 108 108 ...
$ AwayTeamId : int 117 117 117 117 117 117 117 117 117 118 ...
$ Inning : int 1 1 5 1 1 2 1 2 5 4 ...
$ InningTop : int 0 0 0 0 0 0 0 0 0 0 ...
$ PlateAppearance : int 2 2 2 2 2 7 2 7 2 4 ...
$ PitchOfPA : int 4 6 1 1 2 4 3 3 3 1 ...
$ Balls : int 2 3 0 0 0 2 1 2 0 0 ...
$ Strikes : int 1 2 0 0 1 1 1 0 2 0 ...
$ PitchResult : num 0 0 0 0 0 0 0 0 0 0 ...
$ BatterId : int 77171 77171 77171 77171 77171 77171 77171 77171 77171 77171 ...
$ PitcherId : int 64271 64271 64271 64271 64271 64271 64271 64271 64271 31921 ...
$ CatcherId : int 59270 59270 59270 59270 59270 59270 59270 59270 59270 67658 ...
$ UmpireId : int 427248 427248 427248 427248 427248 427248 427248 427248 427248 427156 ...
$ BatSide : Factor w/ 2 levels "L","R": 2 2 2 2 2 2 2 2 2 2 ...
$ PitchHand : Factor w/ 2 levels "L","R": 2 2 2 2 2 2 2 2 2 2 ...
$ PitcherSet : Factor w/ 2 levels "Stretch","Windup": 2 2 1 2 2 1 2 1 1 1 ...
$ PitchType : Factor w/ 2 levels "Fastball","Slider": 1 1 1 1 1 1 1 1 1 1 ...
$ ReleaseSpeed : Factor w/ 163594 levels "100.003","100.004",..: 118138 113206 96757 105450 108863 104792 99623 88801 106163 118932 ...
$ PitchTimeToPlate : num 0.409 0.41 0.412 0.415 0.412 ...
$ SpinAxis : Factor w/ 176445 levels "-0.389885","-0.468337",..: 105104 92644 108361 90391 102961 103650 106045 109234 109359 123561 ...
$ SpinRate : Factor w/ 89264 levels "1002.54","1005.62",..: 51306 60703 54411 46083 47822 32355 50456 49402 47238 44709 ...
$ HorzBreakPFX : num -6.64 -4.49 -7.85 -4.33 -5.69 ...
$ VertBreakPFX : num 8.44 9.62 8.92 10.16 7.95 ...
$ ReleaseHeight : num 5.48 5.4 5.32 5.51 5.53 ...
$ ReleaseSide : num 2.11 2.03 1.82 1.96 2.02 ...
$ Extension : num 5.91 6.18 6.45 5.88 6.07 ...
$ VertApproachAngle: Factor w/ 319725 levels "-0.216948","-0.31733",..: 173138 100071 94338 93526 224459 83541 172155 116761 79538 90746 ...
$ HorzApproachAngle: Factor w/ 409250 levels "-0.0001026","-0.000107",..: 130394 205101 54294 165802 185810 128876 159926 91503 109419 78589 ...
$ bscount : chr "2-1" "3-2" "0-0" "0-0" ...
I am trying to run the following code:
glm(PitchResult ~ ReleaseSpeed + bscount + SpinRate,
data = FastballData1, family = binomial)
However, when I do this it shows this code resulting in 96 GB (which is ridiculous) thus causing R Studio to crash. My guess is it seems this creates a circular reference.
Does anyone have any suggestions on how to fix this? Or any other ways to best calculate the probability of a swinging strike based on the above factors?
r rstudio probability glm
edited Nov 24 '18 at 0:52
user20650
17.1k43468
asked Nov 24 '18 at 0:48
gracergracer
193
1
Perhaps one of your predictors has many levels?? -- can you add the results ofstr(FastballData1)please
– user20650
Nov 24 '18 at 0:50
@user20650 I just edited the post to include it... I have also tried subsetting the data to just included the variables I am looking at and it still crashes.
– gracer
Nov 24 '18 at 0:52
2
okay quick eyeball :SpinRateis a factor with 89264 values, andReleaseSpeedis a factor 163594 levels.This will create 89264 + 163594 new columns when the model matrix is formed. Check that it should be a factor and not numeric.
– user20650
Nov 24 '18 at 0:54
2
There's a bunch actually:ReleaseSpeed, SpinAxis, SpinRate, VertApproachAngle, HorzApproachAngleall should be converted to numeric.
– merv
Nov 24 '18 at 0:56
(ps: it is always good to usestr(yourdata)after reading in. It lets you check that your data is in the expected form i.e. numeric variables are not factor/character etc)
– user20650
Nov 24 '18 at 0:58
|
show 1 more comment
1
1
1
I am trying to find the probability of a Swinging Strike on a various number of factors, including the count, Release Speed, Spin Rate. I have pitch by pitch data. I changed the value of Pitch Result to 0 and 1 (1 being a Swinging Strike, 0 being others). The dataset includes 380,000+ rows.
Data:
str(FastballData1)
'data.frame': 389035 obs. of 30 variables:
$ GameId : int 449257 449257 449257 449257 449257 449257 449257 449257 449257 447167 ...
$ HomeTeamId : int 108 108 108 108 108 108 108 108 108 108 ...
$ AwayTeamId : int 117 117 117 117 117 117 117 117 117 118 ...
$ Inning : int 1 1 5 1 1 2 1 2 5 4 ...
$ InningTop : int 0 0 0 0 0 0 0 0 0 0 ...
$ PlateAppearance : int 2 2 2 2 2 7 2 7 2 4 ...
$ PitchOfPA : int 4 6 1 1 2 4 3 3 3 1 ...
$ Balls : int 2 3 0 0 0 2 1 2 0 0 ...
$ Strikes : int 1 2 0 0 1 1 1 0 2 0 ...
$ PitchResult : num 0 0 0 0 0 0 0 0 0 0 ...
$ BatterId : int 77171 77171 77171 77171 77171 77171 77171 77171 77171 77171 ...
$ PitcherId : int 64271 64271 64271 64271 64271 64271 64271 64271 64271 31921 ...
$ CatcherId : int 59270 59270 59270 59270 59270 59270 59270 59270 59270 67658 ...
$ UmpireId : int 427248 427248 427248 427248 427248 427248 427248 427248 427248 427156 ...
$ BatSide : Factor w/ 2 levels "L","R": 2 2 2 2 2 2 2 2 2 2 ...
$ PitchHand : Factor w/ 2 levels "L","R": 2 2 2 2 2 2 2 2 2 2 ...
$ PitcherSet : Factor w/ 2 levels "Stretch","Windup": 2 2 1 2 2 1 2 1 1 1 ...
$ PitchType : Factor w/ 2 levels "Fastball","Slider": 1 1 1 1 1 1 1 1 1 1 ...
$ ReleaseSpeed : Factor w/ 163594 levels "100.003","100.004",..: 118138 113206 96757 105450 108863 104792 99623 88801 106163 118932 ...
$ PitchTimeToPlate : num 0.409 0.41 0.412 0.415 0.412 ...
$ SpinAxis : Factor w/ 176445 levels "-0.389885","-0.468337",..: 105104 92644 108361 90391 102961 103650 106045 109234 109359 123561 ...
$ SpinRate : Factor w/ 89264 levels "1002.54","1005.62",..: 51306 60703 54411 46083 47822 32355 50456 49402 47238 44709 ...
$ HorzBreakPFX : num -6.64 -4.49 -7.85 -4.33 -5.69 ...
$ VertBreakPFX : num 8.44 9.62 8.92 10.16 7.95 ...
$ ReleaseHeight : num 5.48 5.4 5.32 5.51 5.53 ...
$ ReleaseSide : num 2.11 2.03 1.82 1.96 2.02 ...
$ Extension : num 5.91 6.18 6.45 5.88 6.07 ...
$ VertApproachAngle: Factor w/ 319725 levels "-0.216948","-0.31733",..: 173138 100071 94338 93526 224459 83541 172155 116761 79538 90746 ...
$ HorzApproachAngle: Factor w/ 409250 levels "-0.0001026","-0.000107",..: 130394 205101 54294 165802 185810 128876 159926 91503 109419 78589 ...
$ bscount : chr "2-1" "3-2" "0-0" "0-0" ...
I am trying to run the following code:
glm(PitchResult ~ ReleaseSpeed + bscount + SpinRate,
data = FastballData1, family = binomial)
However, when I do this it shows this code resulting in 96 GB (which is ridiculous) thus causing R Studio to crash. My guess is it seems this creates a circular reference.
Does anyone have any suggestions on how to fix this? Or any other ways to best calculate the probability of a swinging strike based on the above factors?
r rstudio probability glm
edited Nov 24 '18 at 0:52
user20650
17.1k43468
asked Nov 24 '18 at 0:48
gracergracer
193
I am trying to find the probability of a Swinging Strike on a various number of factors, including the count, Release Speed, Spin Rate. I have pitch by pitch data. I changed the value of Pitch Result to 0 and 1 (1 being a Swinging Strike, 0 being others). The dataset includes 380,000+ rows.
Data:
str(FastballData1)
'data.frame': 389035 obs. of 30 variables:
$ GameId : int 449257 449257 449257 449257 449257 449257 449257 449257 449257 447167 ...
$ HomeTeamId : int 108 108 108 108 108 108 108 108 108 108 ...
$ AwayTeamId : int 117 117 117 117 117 117 117 117 117 118 ...
$ Inning : int 1 1 5 1 1 2 1 2 5 4 ...
$ InningTop : int 0 0 0 0 0 0 0 0 0 0 ...
$ PlateAppearance : int 2 2 2 2 2 7 2 7 2 4 ...
$ PitchOfPA : int 4 6 1 1 2 4 3 3 3 1 ...
$ Balls : int 2 3 0 0 0 2 1 2 0 0 ...
$ Strikes : int 1 2 0 0 1 1 1 0 2 0 ...
$ PitchResult : num 0 0 0 0 0 0 0 0 0 0 ...
$ BatterId : int 77171 77171 77171 77171 77171 77171 77171 77171 77171 77171 ...
$ PitcherId : int 64271 64271 64271 64271 64271 64271 64271 64271 64271 31921 ...
$ CatcherId : int 59270 59270 59270 59270 59270 59270 59270 59270 59270 67658 ...
$ UmpireId : int 427248 427248 427248 427248 427248 427248 427248 427248 427248 427156 ...
$ BatSide : Factor w/ 2 levels "L","R": 2 2 2 2 2 2 2 2 2 2 ...
$ PitchHand : Factor w/ 2 levels "L","R": 2 2 2 2 2 2 2 2 2 2 ...
$ PitcherSet : Factor w/ 2 levels "Stretch","Windup": 2 2 1 2 2 1 2 1 1 1 ...
$ PitchType : Factor w/ 2 levels "Fastball","Slider": 1 1 1 1 1 1 1 1 1 1 ...
$ ReleaseSpeed : Factor w/ 163594 levels "100.003","100.004",..: 118138 113206 96757 105450 108863 104792 99623 88801 106163 118932 ...
$ PitchTimeToPlate : num 0.409 0.41 0.412 0.415 0.412 ...
$ SpinAxis : Factor w/ 176445 levels "-0.389885","-0.468337",..: 105104 92644 108361 90391 102961 103650 106045 109234 109359 123561 ...
$ SpinRate : Factor w/ 89264 levels "1002.54","1005.62",..: 51306 60703 54411 46083 47822 32355 50456 49402 47238 44709 ...
$ HorzBreakPFX : num -6.64 -4.49 -7.85 -4.33 -5.69 ...
$ VertBreakPFX : num 8.44 9.62 8.92 10.16 7.95 ...
$ ReleaseHeight : num 5.48 5.4 5.32 5.51 5.53 ...
$ ReleaseSide : num 2.11 2.03 1.82 1.96 2.02 ...
$ Extension : num 5.91 6.18 6.45 5.88 6.07 ...
$ VertApproachAngle: Factor w/ 319725 levels "-0.216948","-0.31733",..: 173138 100071 94338 93526 224459 83541 172155 116761 79538 90746 ...
$ HorzApproachAngle: Factor w/ 409250 levels "-0.0001026","-0.000107",..: 130394 205101 54294 165802 185810 128876 159926 91503 109419 78589 ...
$ bscount : chr "2-1" "3-2" "0-0" "0-0" ...
I am trying to run the following code:
glm(PitchResult ~ ReleaseSpeed + bscount + SpinRate,
data = FastballData1, family = binomial)
However, when I do this it shows this code resulting in 96 GB (which is ridiculous) thus causing R Studio to crash. My guess is it seems this creates a circular reference.
Does anyone have any suggestions on how to fix this? Or any other ways to best calculate the probability of a swinging strike based on the above factors?
r rstudio probability glm
r rstudio probability glm
edited Nov 24 '18 at 0:52
user20650
17.1k43468
asked Nov 24 '18 at 0:48
gracergracer
193
edited Nov 24 '18 at 0:52
user20650
17.1k43468
asked Nov 24 '18 at 0:48
gracergracer
193
edited Nov 24 '18 at 0:52
user20650
17.1k43468
edited Nov 24 '18 at 0:52
user20650
17.1k43468
edited Nov 24 '18 at 0:52
user20650
17.1k43468
17.1k43468
asked Nov 24 '18 at 0:48
gracergracer
193
asked Nov 24 '18 at 0:48
gracergracer
193
asked Nov 24 '18 at 0:48
gracergracer
193
193
1
Perhaps one of your predictors has many levels?? -- can you add the results ofstr(FastballData1)please
– user20650
Nov 24 '18 at 0:50
@user20650 I just edited the post to include it... I have also tried subsetting the data to just included the variables I am looking at and it still crashes.
– gracer
Nov 24 '18 at 0:52
2
okay quick eyeball :SpinRateis a factor with 89264 values, andReleaseSpeedis a factor 163594 levels.This will create 89264 + 163594 new columns when the model matrix is formed. Check that it should be a factor and not numeric.
– user20650
Nov 24 '18 at 0:54
2
There's a bunch actually:ReleaseSpeed, SpinAxis, SpinRate, VertApproachAngle, HorzApproachAngleall should be converted to numeric.
– merv
Nov 24 '18 at 0:56
(ps: it is always good to usestr(yourdata)after reading in. It lets you check that your data is in the expected form i.e. numeric variables are not factor/character etc)
– user20650
Nov 24 '18 at 0:58
|
show 1 more comment
1
Perhaps one of your predictors has many levels?? -- can you add the results ofstr(FastballData1)please
– user20650
Nov 24 '18 at 0:50
@user20650 I just edited the post to include it... I have also tried subsetting the data to just included the variables I am looking at and it still crashes.
– gracer
Nov 24 '18 at 0:52
2
okay quick eyeball :SpinRateis a factor with 89264 values, andReleaseSpeedis a factor 163594 levels.This will create 89264 + 163594 new columns when the model matrix is formed. Check that it should be a factor and not numeric.
– user20650
Nov 24 '18 at 0:54
2
There's a bunch actually:ReleaseSpeed, SpinAxis, SpinRate, VertApproachAngle, HorzApproachAngleall should be converted to numeric.
– merv
Nov 24 '18 at 0:56
(ps: it is always good to usestr(yourdata)after reading in. It lets you check that your data is in the expected form i.e. numeric variables are not factor/character etc)
– user20650
Nov 24 '18 at 0:58
1
1
Perhaps one of your predictors has many levels?? -- can you add the results of
str(FastballData1) please– user20650
Nov 24 '18 at 0:50
Perhaps one of your predictors has many levels?? -- can you add the results of
str(FastballData1) please– user20650
Nov 24 '18 at 0:50
@user20650 I just edited the post to include it... I have also tried subsetting the data to just included the variables I am looking at and it still crashes.
– gracer
Nov 24 '18 at 0:52
@user20650 I just edited the post to include it... I have also tried subsetting the data to just included the variables I am looking at and it still crashes.
– gracer
Nov 24 '18 at 0:52
2
2
okay quick eyeball :
SpinRate is a factor with 89264 values, and ReleaseSpeed is a factor 163594 levels.This will create 89264 + 163594 new columns when the model matrix is formed. Check that it should be a factor and not numeric.– user20650
Nov 24 '18 at 0:54
okay quick eyeball :
SpinRate is a factor with 89264 values, and ReleaseSpeed is a factor 163594 levels.This will create 89264 + 163594 new columns when the model matrix is formed. Check that it should be a factor and not numeric.– user20650
Nov 24 '18 at 0:54
2
2
There's a bunch actually:
ReleaseSpeed, SpinAxis, SpinRate, VertApproachAngle, HorzApproachAngle all should be converted to numeric.– merv
Nov 24 '18 at 0:56
There's a bunch actually:
ReleaseSpeed, SpinAxis, SpinRate, VertApproachAngle, HorzApproachAngle all should be converted to numeric.– merv
Nov 24 '18 at 0:56
(ps: it is always good to use
str(yourdata) after reading in. It lets you check that your data is in the expected form i.e. numeric variables are not factor/character etc)– user20650
Nov 24 '18 at 0:58
(ps: it is always good to use
str(yourdata) after reading in. It lets you check that your data is in the expected form i.e. numeric variables are not factor/character etc)– user20650
Nov 24 '18 at 0:58
|
show 1 more comment
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1
Perhaps one of your predictors has many levels?? -- can you add the results of
str(FastballData1)please– user20650
Nov 24 '18 at 0:50
@user20650 I just edited the post to include it... I have also tried subsetting the data to just included the variables I am looking at and it still crashes.
– gracer
Nov 24 '18 at 0:52
2
okay quick eyeball :
SpinRateis a factor with 89264 values, andReleaseSpeedis a factor 163594 levels.This will create 89264 + 163594 new columns when the model matrix is formed. Check that it should be a factor and not numeric.– user20650
Nov 24 '18 at 0:54
2
There's a bunch actually:
ReleaseSpeed, SpinAxis, SpinRate, VertApproachAngle, HorzApproachAngleall should be converted to numeric.– merv
Nov 24 '18 at 0:56
(ps: it is always good to use
str(yourdata)after reading in. It lets you check that your data is in the expected form i.e. numeric variables are not factor/character etc)– user20650
Nov 24 '18 at 0:58