Polynomial fit functions === === === === RegressionObject.cls contains a class that provides an easy way to add polynomial regression functionality to any application. If you just want linear regression or a very high degree, no matter: this class has good performance and scales seamlessly with the complexity of your problem.
標簽： RegressionObject Polynomial functions contains
上傳時間： 2015-04-06
上傳用戶：rocwangdp
提供了幾種數據擬合的c++代碼：1 直線擬合(fit)；2 線性最小二乘法((Lfit, COVSRT), (SVDfit, SVDVAR)(oddity), (FPOLY, FLEG)(example))；3 非線性最小二乘法((MRQMIN(Levenberg-Marguardt), MRQCOF(evaluation)), FGAUSS(example))；4 絕對值偏差最小的直線擬合(MEDfit(cal para), ROFUNC(example))。
標簽： COVSRT SVDfit SVDVAR oddity
上傳時間： 2014-01-09
上傳用戶：bjgaofei
通過奇異值分解實現的最小二乘擬合算法 inear least-squares fit by singular value decomposition
標簽： decomposition least-squares singular inear
上傳時間： 2015-07-26
上傳用戶：bibirnovis
IF YOUR DESIGN A VIDEO SYSTEM YOU NEEDED IT （INCLUDE A AVIFIL32.DLL) It fit VFW
標簽： INCLUDE DESIGN AVIFIL SYSTEM
上傳時間： 2014-01-05
上傳用戶：jackgao
fit programme for a serials of data
標簽： programme serials data fit
上傳時間： 2013-12-17
上傳用戶：225588
a neural network,Recursive SOM and Marge SOM ,can be use for time series and data fit.
上傳時間： 2013-12-17
上傳用戶：cxl274287265
ICP fit points in data to the points in model. fit with respect to minimize the sum of square errors with the closest model points and data points. Ordinary usage: [R, T] = icp(model,data) INPUT: model - matrix with model points, data - matrix with data points, OUTPUT: R - rotation matrix and T - translation vector accordingly so newdata = R*data + T . newdata are transformed data points to fit model see help icp for more information
標簽： points the minimize respect
上傳時間： 2014-01-02
上傳用戶：gyq
fit a multivariate gaussian mixture by a cross-entropy method. Cross-Entropy is a powerfull tool to achieve stochastic multi-extremum optimization.
標簽： Cross-Entropy cross-entropy multivariate powerfull
上傳時間： 2014-12-20
上傳用戶：love_stanford
多項式曲線擬合 任意介數 Purpose - Least-squares curve fit of arbitrary order working in C++ Builder 2007 as a template class, using vector<FloatType> parameters. Added a method to handle some EMathError exceptions. If do NOT want to use this just call Polyfit2 directly. usage: Call Polyfit by something like this. CPolyfit<double> PolyfitObj double correlation_coefficiant = PolyfitObj.Polyfit(X, Y, A) where X and Y are vectors of doubles which must have the same size and A is a vector of doubles which must be the same size as the number of coefficients required. returns: The correlation coefficient or -1 on failure. produces: A vector (A) which holds the coefficients.
標簽： Least-squares arbitrary Purpose Builder
上傳時間： 2013-12-18
上傳用戶：宋桃子
首次適應算法（First fit）： 從空閑分區表的第一個表目起查找該表，把最先能夠滿足要求的空閑區分配給作業，這種方法目的在于減少查找時間。為適應這種算法，空閑分區表（空閑區鏈）中的空閑分區要按地址由低到高進行排序。該算法優先使用低址部分空閑區，在低址空間造成許多小的空閑區，在高地址空間保留大的空閑區。
上傳時間： 2014-01-08
上傳用戶：1051290259
