Skip to content

[SPARK-23461][R]vignettes should include model predictions for some ML models #21678

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
huaxingao wants to merge 1 commit into from
Closed

[SPARK-23461][R]vignettes should include model predictions for some ML models #21678

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
5 changes: 5 additions & 0 deletions R/pkg/vignettes/sparkr-vignettes.Rmd
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -590,6 +590,7 @@ summary(model)
Predict values on training data
```{r}
prediction <- predict(model, training)
head(select(prediction, "Class", "Sex", "Age", "Freq", "Survived", "prediction"))
```

#### Logistic Regression
Expand All @@ -613,6 +614,7 @@ summary(model)
Predict values on training data
```{r}
fitted <- predict(model, training)
head(select(fitted, "Class", "Sex", "Age", "Freq", "Survived", "prediction"))
```

Multinomial logistic regression against three classes
Expand Down Expand Up @@ -807,6 +809,7 @@ df <- createDataFrame(t)
dtModel <- spark.decisionTree(df, Survived ~ ., type = "classification", maxDepth = 2)
summary(dtModel)
predictions <- predict(dtModel, df)
head(select(predictions, "Class", "Sex", "Age", "Freq", "Survived", "prediction"))
```

#### Gradient-Boosted Trees
Expand All @@ -822,6 +825,7 @@ df <- createDataFrame(t)
gbtModel <- spark.gbt(df, Survived ~ ., type = "classification", maxDepth = 2, maxIter = 2)
summary(gbtModel)
predictions <- predict(gbtModel, df)
head(select(predictions, "Class", "Sex", "Age", "Freq", "Survived", "prediction"))
```

#### Random Forest
Expand All @@ -837,6 +841,7 @@ df <- createDataFrame(t)
rfModel <- spark.randomForest(df, Survived ~ ., type = "classification", maxDepth = 2, numTrees = 2)
summary(rfModel)
predictions <- predict(rfModel, df)
head(select(predictions, "Class", "Sex", "Age", "Freq", "Survived", "prediction"))
```

#### Bisecting k-Means
Expand Down