Logistic Regression: A multivariate logistic regression model has been built to predict the classification of texts. The label is binary with $1$ being positive and $0$ being negative. The descriptive features used by the model and their initial weights are as follows:

Given the following text, please extract the feature values of $\backslash ($ x$\_\{1\}\backslash )$ and $\backslash ($ x$\_\{2\}\backslash ),$ and use the logistic regression model to calculate its prediction result. If the true label of the text is $0($negative$)$ and the loss function is cross$-$entropy, use stochastic gradient descent and learning rate $\backslash (\backslash$eta$=0\mathrm{.}1\backslash )$ to update the weights one epoch and recalculate the prediction using the new weights. Show your calculations.

"The short boy runs fast"