Пример #1
0
        /// <summary>
        ///   Selects an optimal combination of features to classify the provided data.
        ///   Instance represents: Handle of the training data.
        /// </summary>
        /// <param name="selectionMethod">Method to perform the selection. Default: "greedy"</param>
        /// <param name="genParamName">Names of generic parameters to configure the  selection process and the classifier. Default: []</param>
        /// <param name="genParamValue">Values of generic parameters to configure the  selection process and the classifier. Default: []</param>
        /// <param name="selectedFeatureIndices">The selected feature set, contains  indices.</param>
        /// <param name="score">The achieved score using two-fold cross-validation.</param>
        /// <returns>A trained SVM classifier using only the selected  features.</returns>
        public HClassSvm SelectFeatureSetSvm(
            string selectionMethod,
            string genParamName,
            double genParamValue,
            out HTuple selectedFeatureIndices,
            out HTuple score)
        {
            IntPtr proc = HalconAPI.PreCall(1800);

            this.Store(proc, 0);
            HalconAPI.StoreS(proc, 1, selectionMethod);
            HalconAPI.StoreS(proc, 2, genParamName);
            HalconAPI.StoreD(proc, 3, genParamValue);
            HalconAPI.InitOCT(proc, 0);
            HalconAPI.InitOCT(proc, 1);
            HalconAPI.InitOCT(proc, 2);
            int       err1 = HalconAPI.CallProcedure(proc);
            HClassSvm hclassSvm;
            int       err2       = HClassSvm.LoadNew(proc, 0, err1, out hclassSvm);
            int       err3       = HTuple.LoadNew(proc, 1, err2, out selectedFeatureIndices);
            int       procResult = HTuple.LoadNew(proc, 2, HTupleType.DOUBLE, err3, out score);

            HalconAPI.PostCall(proc, procResult);
            GC.KeepAlive((object)this);
            return(hclassSvm);
        }
Пример #2
0
        /// <summary>
        ///   Approximate a trained support vector machine by a reduced support vector machine for faster classification.
        ///   Instance represents: Original SVM handle.
        /// </summary>
        /// <param name="method">Type of postprocessing to reduce number of SV. Default: "bottom_up"</param>
        /// <param name="minRemainingSV">Minimum number of remaining SVs. Default: 2</param>
        /// <param name="maxError">Maximum allowed error of reduction. Default: 0.001</param>
        /// <returns>SVMHandle of reduced SVM.</returns>
        public HClassSvm ReduceClassSvm(string method, int minRemainingSV, double maxError)
        {
            IntPtr proc = HalconAPI.PreCall(1852);

            this.Store(proc, 0);
            HalconAPI.StoreS(proc, 1, method);
            HalconAPI.StoreI(proc, 2, minRemainingSV);
            HalconAPI.StoreD(proc, 3, maxError);
            HalconAPI.InitOCT(proc, 0);
            int       err = HalconAPI.CallProcedure(proc);
            HClassSvm hclassSvm;
            int       procResult = HClassSvm.LoadNew(proc, 0, err, out hclassSvm);

            HalconAPI.PostCall(proc, procResult);
            GC.KeepAlive((object)this);
            return(hclassSvm);
        }