| /dports/math/mlpack/mlpack-3.4.2/src/mlpack/tests/main_tests/ |
| H A D | logistic_regression_test.cpp | 73 arma::mat trainX = arma::randu<arma::mat>(D, N); in BOOST_AUTO_TEST_CASE() local
74 SetInputParam("training", std::move(trainX)); in BOOST_AUTO_TEST_CASE()
98 SetInputParam("training", std::move(trainX)); in BOOST_AUTO_TEST_CASE()
128 SetInputParam("training", std::move(trainX)); in BOOST_AUTO_TEST_CASE()
199 SetInputParam("training", std::move(trainX)); in BOOST_AUTO_TEST_CASE()
410 SetInputParam("training", trainX); in BOOST_AUTO_TEST_CASE()
459 SetInputParam("training", trainX); in BOOST_AUTO_TEST_CASE()
508 SetInputParam("training", trainX); in BOOST_AUTO_TEST_CASE()
559 SetInputParam("training", trainX); in BOOST_AUTO_TEST_CASE()
613 SetInputParam("training", trainX); in BOOST_AUTO_TEST_CASE()
[all …]
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| H A D | linear_regression_test.cpp | 60 arma::mat trainX({1.0, 2.0, 3.0}); variable
64 SetInputParam("training", trainX);
76 SetInputParam("training", std::move(trainX));
136 arma::mat trainX = arma::randu<arma::mat>(D, N); variable
140 SetInputParam("training", std::move(trainX));
171 arma::mat trainX = arma::randu<arma::mat>(D, N); variable
174 SetInputParam("training", std::move(trainX));
196 SetInputParam("training", std::move(trainX));
218 SetInputParam("training", std::move(trainX));
250 SetInputParam("training", std::move(trainX));
[all …]
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| H A D | perceptron_test.cpp | 333 arma::mat trainX = arma::randu<arma::mat>(D, N); in BOOST_AUTO_TEST_CASE() local
342 SetInputParam("training", std::move(trainX)); in BOOST_AUTO_TEST_CASE()
360 arma::mat trainX = arma::randu<arma::mat>(D, N); in BOOST_AUTO_TEST_CASE() local
366 SetInputParam("training", std::move(trainX)); in BOOST_AUTO_TEST_CASE()
383 arma::mat trainX = arma::randu<arma::mat>(D, N); in BOOST_AUTO_TEST_CASE() local
384 SetInputParam("training", std::move(trainX)); in BOOST_AUTO_TEST_CASE()
417 arma::mat trainX = arma::randu<arma::mat>(D, N); in BOOST_AUTO_TEST_CASE() local
423 SetInputParam("training", std::move(trainX)); in BOOST_AUTO_TEST_CASE()
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| /dports/graphics/opencv/opencv-4.5.3/contrib/modules/wechat_qrcode/src/zxing/common/ |
| H A D | kmeans.cpp | 35 vector<Cluster> k_means(vector<vector<double> > trainX, uint k, uint maxepoches, uint minchanged) { in k_means() argument
36 const uint row_num = trainX.size(); in k_means()
37 const uint col_num = trainX[0].size(); in k_means()
41 int step = trainX.size() / k; in k_means()
44 clusters[i].centroid = trainX[i * step]; in k_means()
54 double min_distance = cal_distance(trainX[j], clusters[c].centroid); in k_means()
56 double distance = cal_distance(trainX[j], clusters[i].centroid); in k_means()
72 val[d] += trainX[sample][d]; in k_means()
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| H A D | kmeans.hpp | 23 vector<Cluster> k_means(vector<vector<double> > trainX, uint k, uint maxepoches, uint minchanged);
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| /dports/devel/R-cran-caret/caret/man/ |
| H A D | plotObsVsPred.Rd | 71 trainX <- Satellite[trainSamples, -37]
79 knnFit <- train(trainX, trainY, "knn")
80 rpartFit <- train(trainX, trainY, "rpart")
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| H A D | knnreg.Rd | 77 trainX <- bbbDescr[inTrain,]
83 fit <- knnreg(trainX, trainY, k = 3)
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| H A D | calibration.Rd | 108 trainX <- mdrrDescr[inTrain[[1]], ]
115 ldaFit <- lda(trainX, trainY)
116 qdaFit <- qda(trainX, trainY)
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| /dports/games/openbve/OpenBVE-1.8.2.1/source/OpenBVE/Game/ |
| H A D | RouteInfoOverlay.cs | 88 int trainX = (int)Program.TrainManager.Trains[i].Cars[0].FrontAxle.Follower.WorldPosition.X; in Show()
91 xPos = mapSize.X * (trainX - Program.CurrentRoute.Information.RouteMinX) / in Show()
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| /dports/misc/mxnet/incubator-mxnet-1.9.0/docs/static_site/src/pages/api/r/docs/tutorials/ |
| H A D | multi_dim_lstm.md | 116 trainX <- trX
117 dim(trainX) <- c(n_dim, seq_len, num_samples)
136 train.data <- mx.io.arrayiter(data = trainX[, , train_ids, drop = F],
140 eval.data <- mx.io.arrayiter(data = trainX[, , eval_ids, drop = F],
270 data <- mx.nd.array(trainX[, , 400, drop = F])
296 data <- mx.nd.array(trainX[, i, 401, drop = F])
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| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/docs/static_site/src/pages/api/r/docs/tutorials/ |
| H A D | multi_dim_lstm.md | 116 trainX <- trX
117 dim(trainX) <- c(n_dim, seq_len, num_samples)
136 train.data <- mx.io.arrayiter(data = trainX[, , train_ids, drop = F],
140 eval.data <- mx.io.arrayiter(data = trainX[, , eval_ids, drop = F],
270 data <- mx.nd.array(trainX[, , 400, drop = F])
296 data <- mx.nd.array(trainX[, i, 401, drop = F])
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| /dports/devel/R-cran-caret/caret/R/ |
| H A D | extractProb.R | 23 …trainX <- models[[1]]$trainingData[,!(colnames(models[[1]]$trainingData) %in% ".outcome"), drop = … functionVar
47 trainX,
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| H A D | extractPrediction.R | 15 …trainX <- models[[1]]$trainingData[,!(colnames(models[[1]]$trainingData) %in% ".outcome"), drop = … functionVar
40 trainX,
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| /dports/graphics/opencv/opencv-4.5.3/contrib/modules/wechat_qrcode/src/zxing/qrcode/detector/ |
| H A D | finder_pattern_finder.cpp | 478 vector<vector<double>> trainX; in getPatternInfosFileMode() local
483 trainX.push_back(tmp); in getPatternInfosFileMode()
486 vector<Cluster> clusters_out = k_means(trainX, k, maxepoches, minchanged); in getPatternInfosFileMode()
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| /dports/games/openrct2/OpenRCT2-0.3.5.1/src/openrct2/ride/ |
| H A D | Vehicle.cpp | 3536 int32_t trainX = stru_9A3AC4[trainVehicle->sprite_direction / 2].x; in UpdateCrashSetup() local
3541 trainX *= ecx; in UpdateCrashSetup()
3543 trainX >>= 16; in UpdateCrashSetup()
3545 trainX *= edx; in UpdateCrashSetup()
3548 trainX >>= 8; in UpdateCrashSetup()
3552 trainVehicle->crash_x = trainX; in UpdateCrashSetup()
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