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author | Felix Cheung <felixcheung_m@hotmail.com> | 2017-01-10 11:42:07 -0800 |
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committer | Felix Cheung <felixcheung@apache.org> | 2017-01-10 11:42:07 -0800 |
commit | 9bc3507e411b0ad9207e3053f80ac82f19b18f26 (patch) | |
tree | 05b787ff541d809eef4913b0c61824556ff3fd9b /R/pkg/inst | |
parent | d5b1dc934a2482886c2c095de90e4c6a49ec42bd (diff) | |
download | spark-9bc3507e411b0ad9207e3053f80ac82f19b18f26.tar.gz spark-9bc3507e411b0ad9207e3053f80ac82f19b18f26.tar.bz2 spark-9bc3507e411b0ad9207e3053f80ac82f19b18f26.zip |
[SPARK-19133][SPARKR][ML] fix glm for Gamma, clarify glm family supported
## What changes were proposed in this pull request?
R family is a longer list than what Spark supports.
## How was this patch tested?
manual
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes #16511 from felixcheung/rdocglmfamily.
Diffstat (limited to 'R/pkg/inst')
-rw-r--r-- | R/pkg/inst/tests/testthat/test_mllib_regression.R | 26 |
1 files changed, 17 insertions, 9 deletions
diff --git a/R/pkg/inst/tests/testthat/test_mllib_regression.R b/R/pkg/inst/tests/testthat/test_mllib_regression.R index e20dafa414..c450a15171 100644 --- a/R/pkg/inst/tests/testthat/test_mllib_regression.R +++ b/R/pkg/inst/tests/testthat/test_mllib_regression.R @@ -61,14 +61,22 @@ test_that("spark.glm and predict", { # poisson family model <- spark.glm(training, Sepal_Width ~ Sepal_Length + Species, - family = poisson(link = identity)) + family = poisson(link = identity)) prediction <- predict(model, training) expect_equal(typeof(take(select(prediction, "prediction"), 1)$prediction), "double") vals <- collect(select(prediction, "prediction")) rVals <- suppressWarnings(predict(glm(Sepal.Width ~ Sepal.Length + Species, - data = iris, family = poisson(link = identity)), iris)) + data = iris, family = poisson(link = identity)), iris)) expect_true(all(abs(rVals - vals) < 1e-6), rVals - vals) + # Gamma family + x <- runif(100, -1, 1) + y <- rgamma(100, rate = 10 / exp(0.5 + 1.2 * x), shape = 10) + df <- as.DataFrame(as.data.frame(list(x = x, y = y))) + model <- glm(y ~ x, family = Gamma, df) + out <- capture.output(print(summary(model))) + expect_true(any(grepl("Dispersion parameter for gamma family", out))) + # Test stats::predict is working x <- rnorm(15) y <- x + rnorm(15) @@ -103,11 +111,11 @@ test_that("spark.glm summary", { df <- suppressWarnings(createDataFrame(iris)) training <- df[df$Species %in% c("versicolor", "virginica"), ] stats <- summary(spark.glm(training, Species ~ Sepal_Length + Sepal_Width, - family = binomial(link = "logit"))) + family = binomial(link = "logit"))) rTraining <- iris[iris$Species %in% c("versicolor", "virginica"), ] rStats <- summary(glm(Species ~ Sepal.Length + Sepal.Width, data = rTraining, - family = binomial(link = "logit"))) + family = binomial(link = "logit"))) coefs <- unlist(stats$coefficients) rCoefs <- unlist(rStats$coefficients) @@ -222,7 +230,7 @@ test_that("glm and predict", { training <- suppressWarnings(createDataFrame(iris)) # gaussian family model <- glm(Sepal_Width ~ Sepal_Length + Species, data = training) - prediction <- predict(model, training) + prediction <- predict(model, training) expect_equal(typeof(take(select(prediction, "prediction"), 1)$prediction), "double") vals <- collect(select(prediction, "prediction")) rVals <- predict(glm(Sepal.Width ~ Sepal.Length + Species, data = iris), iris) @@ -235,7 +243,7 @@ test_that("glm and predict", { expect_equal(typeof(take(select(prediction, "prediction"), 1)$prediction), "double") vals <- collect(select(prediction, "prediction")) rVals <- suppressWarnings(predict(glm(Sepal.Width ~ Sepal.Length + Species, - data = iris, family = poisson(link = identity)), iris)) + data = iris, family = poisson(link = identity)), iris)) expect_true(all(abs(rVals - vals) < 1e-6), rVals - vals) # Test stats::predict is working @@ -268,11 +276,11 @@ test_that("glm summary", { df <- suppressWarnings(createDataFrame(iris)) training <- df[df$Species %in% c("versicolor", "virginica"), ] stats <- summary(glm(Species ~ Sepal_Length + Sepal_Width, data = training, - family = binomial(link = "logit"))) + family = binomial(link = "logit"))) rTraining <- iris[iris$Species %in% c("versicolor", "virginica"), ] rStats <- summary(glm(Species ~ Sepal.Length + Sepal.Width, data = rTraining, - family = binomial(link = "logit"))) + family = binomial(link = "logit"))) coefs <- unlist(stats$coefficients) rCoefs <- unlist(rStats$coefficients) @@ -409,7 +417,7 @@ test_that("spark.survreg", { x = c(0, 2, 1, 1, 1, 0, 0), sex = c(0, 0, 0, 0, 1, 1, 1)) expect_error( model <- survival::survreg(formula = survival::Surv(time, status) ~ x + sex, data = rData), - NA) + NA) expect_equal(predict(model, rData)[[1]], 3.724591, tolerance = 1e-4) } }) |