> For the complete documentation index, see [llms.txt](https://lab-of-ontologies-language-proce.gitbook.io/ladsbook/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://lab-of-ontologies-language-proce.gitbook.io/ladsbook/part-iii-wen-ben-fen-xi-ying-yong-yu-bao-gao/regression.md).

# 文本迴歸預測

regression model

Text regression using `tm` and `glmnet`

## 簡單線型迴歸

##

## 線性迴歸 with R

```
# Load Train and Test datasets
# Identify feature and response variable(s);values must be numeric

x_train <- input_variables_values_training_datasets 
y_train <- target_variables_values_training_datasets 
x_test <- input_variables_values_test_datasets
x <- cbind(x_train, y_train)

# Train the model using the training sets and check score
linear <- lm(y_train ~ ., data = x)
summary(linear)
# Predict Output
predicted <- predict(linear,x_test)
```

## Logistic 迴歸 with R

```
# Train the model using the training sets and check score
logistic <- glm(y_train ~ ., data = x,family = 'binomial')
summary(logistic)
# Predict Output
predicted <- predict(logistic, x_test)
```

## 多元（複）迴歸模型

* 多了許多預測變數