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例 13053: « インストール手順 SVM » PHP Manual SVM 例検索例 The basic process is to define parameters, supply training data to generate a model on, then make predictions based on the model. There are a default set of parameters that should get some ... > value sets for the feature values pairs. This data is passed to the SVM class's train function, which will return an SVM model is successful. Once a model has been generated, it can be used to make predictions about previously unseen data. This can ... be passed as an array to the model's predict function, in the same format as before, but without the label. The response will be the class. Models can be sav ... array(- 1 , 1 => 0.43 , 3 => 0.12 , 9284 => 0.2 ), array( 1 , 1 => 0.22 , 5 => 0.01 , 94 => 0.11 ), ); $svm = new SVM (); $model = $svm -> train ( $data ); $data = array( 1 => 0.43 , 3 => 0.12 , 9284 => 0.2 ); $result = $model -> predict ( $data ); va ...; https://man.mtool.work/php/8.3/svm.examples.html

例 13053: « インストール手順 SVM » PHP Manual SVM 例検索例 The basic process is to define parameters, supply training data to generate a model on, then make predictions based on the model. There are a default set of parameters that should get some ... > value sets for the feature values pairs. This data is passed to the SVM class's train function, which will return an SVM model is successful. Once a model has been generated, it can be used to make predictions about previously unseen data. This can ... be passed as an array to the model's predict function, in the same format as before, but without the label. The response will be the class. Models can be sav ... array(- 1 , 1 => 0.43 , 3 => 0.12 , 9284 => 0.2 ), array( 1 , 1 => 0.22 , 5 => 0.01 , 94 => 0.11 ), ); $svm = new SVM (); $model = $svm -> train ( $data ); $data = array( 1 => 0.43 , 3 => 0.12 , 9284 => 0.2 ); $result = $model -> predict ( $data ); va ...; https://man.mtool.work/php/8.3/svm.examples.html

Philosophy 10097: « Installation Functional API » PHP Manual parallel Philosophy 検索 Philosophy This section contains philosophies important to writing parallel code and some details about the internal implementation of parallel. Do not communicate by shari ... live up to this ideal: PHP and parallel do all the hard work for the programmer, and by default. In conventional threading models found in other languages, generally threads are communicating with one another through nothing more than by virtue of the ... ding or synchronization primitives in order to ensure proper communication of state and consistency. When the conventional model is inversed, it means that threads only share memory as a result of communication (a variable is passed over a Channel for ... they are no longer sharing memory. This makes writing and reasoning about parallel code much easier than the conventional model of threading. It means the programmer does not need to consider that threads may be manipulating data concurrently, becaus ...; https://man.mtool.work/php/8.3/philosophy.parallel.html

Philosophy 10097: « Installation Functional API » PHP Manual parallel Philosophy 検索 Philosophy This section contains philosophies important to writing parallel code and some details about the internal implementation of parallel. Do not communicate by shari ... live up to this ideal: PHP and parallel do all the hard work for the programmer, and by default. In conventional threading models found in other languages, generally threads are communicating with one another through nothing more than by virtue of the ... ding or synchronization primitives in order to ensure proper communication of state and consistency. When the conventional model is inversed, it means that threads only share memory as a result of communication (a variable is passed over a Channel for ... they are no longer sharing memory. This makes writing and reasoning about parallel code much easier than the conventional model of threading. It means the programmer does not need to consider that threads may be manipulating data concurrently, becaus ...; https://man.mtool.work/php/8.3/philosophy.parallel.html

Return class probabilities for previous unseen data 9794: « SVMModel::predict SVMModel::save » PHP Manual SVMModel Return class probabilities for previous unseen data 検索 SVMModel::predict_probability (PECL svm >= 0.1.4) SVMModel::predict_probability — Return class probabilities for previous unse ... en data 説明 public function SVMModel::predict_probability ( array $data ): float This function accepts an array of data and attempts to predict the class, as w ... ith the predict function. Additionally, however, this function returns an array of probabilities, one per class in the model, which represent the estimated chance of the data supplied being a member of that class. Requires that the model to be use ... inuous. probabilities The supplied value will be filled with the probabilities. This will be either null, in the case of a model without probability information, or an array where the index is the class name and the value the predicted probability. 戻 ...; https://man.mtool.work/php/8.3/svmmodel.predict-probability.html

Return class probabilities for previous unseen data 9794: « SVMModel::predict SVMModel::save » PHP Manual SVMModel Return class probabilities for previous unseen data 検索 SVMModel::predict_probability (PECL svm >= 0.1.4) SVMModel::predict_probability — Return class probabilities for previous unse ... en data 説明 public function SVMModel::predict_probability ( array $data ): float This function accepts an array of data and attempts to predict the class, as w ... ith the predict function. Additionally, however, this function returns an array of probabilities, one per class in the model, which represent the estimated chance of the data supplied being a member of that class. Requires that the model to be use ... inuous. probabilities The supplied value will be filled with the probabilities. This will be either null, in the case of a model without probability information, or an array where the index is the class name and the value the predicted probability. 戻 ...; https://man.mtool.work/php/8.3/svmmodel.predict-probability.html

Manually release stream flow from logger 8867: « SeasLog::analyzerDetail SeasLog::__construct » PHP Manual SeasLog Manually release stream flow from logger 検索 SeasLog::closeLoggerStream (PECL seaslog >=1.8.6) SeasLog::closeLoggerStream — Manually release stream flow from logger 説明 p ... ublic static function SeasLog::closeLoggerStream ( int $model , string $logger ): bool Manually release stream flow from logger. SeasLog caches the stream handle opened by the log logg ... wing functions to manually release(manually release function needs to update SeasLog 1.8.6 or updated version). パラメータ model Constant int. SEASLOG_CLOSE_LOGGER_STREAM_MOD_ALL SEASLOG_CLOSE_LOGGER_STREAM_MOD_ASSIGN logger The logger name. 戻り値 Re ... er path 関連キーワード: SeasLog logger release stream closeLoggerStream flow Manually bool name var dump true function int model handle automatically released manually analyzerDetail ...; https://man.mtool.work/php/8.3/seaslog.closeloggerstream.html

Manually release stream flow from logger 8867: « SeasLog::analyzerDetail SeasLog::__construct » PHP Manual SeasLog Manually release stream flow from logger 検索 SeasLog::closeLoggerStream (PECL seaslog >=1.8.6) SeasLog::closeLoggerStream — Manually release stream flow from logger 説明 p ... ublic static function SeasLog::closeLoggerStream ( int $model , string $logger ): bool Manually release stream flow from logger. SeasLog caches the stream handle opened by the log logg ... wing functions to manually release(manually release function needs to update SeasLog 1.8.6 or updated version). パラメータ model Constant int. SEASLOG_CLOSE_LOGGER_STREAM_MOD_ALL SEASLOG_CLOSE_LOGGER_STREAM_MOD_ASSIGN logger The logger name. 戻り値 Re ... Logger() - Get SeasLog last logger path 関連キーワード: SeasLog logger release stream closeLoggerStream flow Manually dump model handle automatically released manually analyzerDetail construct seaslog static caches opened save overhead creating reques ...; https://man.mtool.work/php/8.3/seaslog.closeloggerstream.html

Predict a value for previously unseen data 8436: « SVMModel::load SVMModel::predict_probability » PHP Manual SVMModel Predict a value for previously unseen data 検索 SVMModel::predict (PECL svm >= 0.1.0) SVMModel::predict — Predict a value for previously unseen data 説明 public function S ... VMModel::predict ( array $data ): float This function accepts an array of data and attempts to predict the class or regression val ... ue based on the model extracted from previously trained data. パラメータ data The array to be classified. This should be a series of key => valu ... se of classification, a real value in the case of regression. Throws SVMException on error 参考 SVM::train() - Create a SVMModel based on training data 関連キーワード: SVMModel predict previously Predict unseen regression based case load probability f ...; https://man.mtool.work/php/8.3/svmmodel.predict.html

Yaf_Loader クラス 8068: « Yaf_View_Simple::setScriptPath Yaf_Loader::autoload » PHP Manual Yaf Yaf_Loader クラス検索 Yaf_Loader クラス (Yaf >=1.0.0) はじめに Yaf_Loader は、 Yaf 用に包括的なオートローディング機能を導入します。最初に Yaf_Application のインスタンス ... も作られています。次のような規約に従います。例5 MVC クラスのロード Controller Classes => // APPLICATION_PATH/controllers/ Model Classes => // APPLICATION_PATH/models/ Plugin Classes => // APPLICATION_PATH/plugins/ クラスのサフィックス (デフォルト設定 ... します) で、MVC クラスであるかそうでないかを判断します。例6 MVC クラスかどうかの区別 Controller Classes => // ***Controller Model Classes => // ***Model Plugin Classes => // ***Plugin 例を示します。例7 MVC のロード class IndexController // APPLICATION ... _PATH/controllers/Index.php class DataModel => // APPLICATION_PATH/models/Data.php class DummyPlugin => // APPLICATION_PATH/plugins/Dummy.php class A_B_TestModel => / ...; https://man.mtool.work/php/8.3/class.yaf-loader.html

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