TensorFlow prices forecast
• Rate Forecast Model Description
Pre-knowledge: supervised learning (Supervised Learning)
It is a supervised learning method machine learning, measured from the training data (inputs and expected outputs) to a middle school model (function),
The new method and the model instance can be inferred.
Output of the function is generally a continuous value (regression analysis) or class label (classification).
Pre-knowledge: Typical supervised learning algorithm
• Linear Regression (Linear Regression)
• logistic regression (Logistic Regression)
• decision tree (Decision Tree)
• Random Forest (Random Forest)
• nearest neighbor (k-NN)
• Naive Bayes (Naive Bayes)
• Support Vector Machine (SVM)
• Sensor (Perceptron)
• Deep Neural Network (DNN)
Pre-knowledge: Linear Regression
In statistics, linear least squares regression using the function called linear regression equation for the one or more independent variables and the dependent variable
A return to the relationship between the amount of modeling analysis. This function is referred to as a combination of one or more linear model parameter regression coefficients.
Pre-knowledge: Univariate linear regression
Ideal function:
• Use TensorFlow realization rate forecasting model
• TensorBoard using a visual model of the data flow in FIG.
• combat TensorFlow prices forecast