def fit_sgd(self, X_train, y_train, n_iters=50, t0=5, t1=50): """根据训练数据集X_train, y_train, 使用梯度下降法训练Linear Regression模型""" assert X_train.shape[0] == y_train.shape[0], "the size of X_train must be equal to the size of y_train" assert n_iters >= 1 ...
Linear regressionGas turbine (GT) power plants suffer from sensitivity to ambient-air temperature, high fuel consumption, and a high amount of waste heat dumped into the ambient. Various solutions were proposed to solve these drawbacks, which could simultaneously solve at most two problems, usually...
linear programmingregressionobjective-aligned fittingWe study an approach to regression that we call objective-aligned fitting, which is applicable when the regression model is used to predict uncertain parametersdoi:10.2139/ssrn.3469897Estes, Alexander...
Problem Solving Using Linear Regression: Steps & Examples from Chapter 8 / Lesson 2 152K Linear regression is a process used to model and evaluate the relationship between dependent and independent variables. Learn about problem solving using linear regression by exploring the steps in the process...
The work ofCandanedo et al. (2018)presents an example, where theroot mean square error(RMSE) is used as the KPI for assessing the learning ability of linear regression (LM) and random forest (RF) algorithms when predicting average indoor temperatures on the basis of incomplete data. The expe...
MOEA/D is a general-purpose algorithm framework. It decomposes a multi-objective optimization problem into a number of single-objective optimization sub-problems and then uses a search heuristic to optimize these sub-problems simultaneously and cooperatively. ...
AIToolbox - A toolbox of AI modules written in Swift: Graphs/Trees, Linear Regression, Support Vector Machines, Neural Networks, PCA, KMeans, Genetic Algorithms, MDP, Mixture of Gaussians. Tensorflow-iOS - The official Google-built powerful neural network library port for iOS. Bender - Easily...
Inferring real-valued workload from real-valued physiological data is a specific example of a more general activity known as regression. Three supervised-learning regression algorithms were evaluated for their ability to infer workload from physio- logical data: linear regression, model trees, and ...
Additionally, a linear regression model was trained on the objective values of the solutions obtained from all 10 runs of each algorithm according to eq. 21. This was to determine the empirical weights of the objectives among the final solutions and examine the balance between requirements. The ...
Binary logit and linear regression models, using objective measures, perceived measures, and both sets of measures, were estimated to predict propensity of bicycling and frequency of bicycling separately. Results showed that the perceived environment and objective environment had different associations with...