AngelMLConf

Value Members

final def !=(arg0: Any): Boolean

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final def ##(): Int

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val ANGEL_COMPRESS_BYTES: String
val ANGEL_ML_INC_TRAIN: String
val ANGEL_ML_PREDICT: String
val ANGEL_ML_TRAIN: String
val ANGEL_WORKER_THREAD_NUM: String
val DEFAULT_ANGEL_COMPRESS_BYTES: Int
val DEFAULT_ANGEL_WORKER_THREAD_NUM: Int
val DEFAULT_KMEANS_C: Double
val DEFAULT_KMEANS_CENTER_NUM: Int
val DEFAULT_ML_AUTO_TUNER_ITER: Int
val DEFAULT_ML_AUTO_TUNER_MINIMIZE: Boolean
val DEFAULT_ML_AUTO_TUNER_MODEL: String
val DEFAULT_ML_BATCH_SAMPLE_RATIO: Double
val DEFAULT_ML_BLOCK_SIZE: Int
val DEFAULT_ML_DATA_HAS_LABEL: Boolean
val DEFAULT_ML_DATA_INPUT_FORMAT: String
val DEFAULT_ML_DATA_LABEL_TRANS: String
val DEFAULT_ML_DATA_LABEL_TRANS_THRESHOLD: Int
val DEFAULT_ML_DATA_POSNEG_RATIO: Int
val DEFAULT_ML_DATA_SPLITOR: String
val DEFAULT_ML_DATA_USE_SHUFFLE: Boolean
val DEFAULT_ML_DECAY_INTERVALS: Int
val DEFAULT_ML_EMBEDDING_OPTIMIZER: String
val DEFAULT_ML_EPOCH_NUM: Int
val DEFAULT_ML_FCLAYER_OPTIMIZER: String
val DEFAULT_ML_FEATURE_INDEX_RANGE: Int
val DEFAULT_ML_FIELD_NUM: Int
val DEFAULT_ML_GBDT_BATCH_SIZE: Int
val DEFAULT_ML_GBDT_CATE_FEAT: String
val DEFAULT_ML_GBDT_CLASS_NUM: Int
val DEFAULT_ML_GBDT_EVAL_METRIC: String
val DEFAULT_ML_GBDT_FEATURE_SAMPLE_RATIO: Double
val DEFAULT_ML_GBDT_FULL_HESSIAN: Boolean
val DEFAULT_ML_GBDT_HIST_SUBTRACTION: Boolean
val DEFAULT_ML_GBDT_LIGHTER_CHILD_FIRST: Boolean
val DEFAULT_ML_GBDT_LOSS_FUNCTION: String
val DEFAULT_ML_GBDT_MAX_LEAF_WEIGHT: Double
val DEFAULT_ML_GBDT_MIN_CHILD_WEIGHT: Double
val DEFAULT_ML_GBDT_MIN_NODE_INSTANCE: Int
val DEFAULT_ML_GBDT_MIN_SPLIT_GAIN: Double
val DEFAULT_ML_GBDT_PARALLEL_MODE: String
val DEFAULT_ML_GBDT_REG_ALPHA: Int
val DEFAULT_ML_GBDT_REG_LAMBDA: Double
val DEFAULT_ML_GBDT_ROW_SAMPLE_RATIO: Int
val DEFAULT_ML_GBDT_SAMPLE_RATIO: Int
val DEFAULT_ML_GBDT_SERVER_SPLIT: Boolean
val DEFAULT_ML_GBDT_SPLIT_NUM: Int
val DEFAULT_ML_GBDT_TASK_TYPE: String
val DEFAULT_ML_GBDT_THREAD_NUM: Int
val DEFAULT_ML_GBDT_TREE_DEPTH: Int
val DEFAULT_ML_GBDT_TREE_NUM: Int
val DEFAULT_ML_INPUTLAYER_OPTIMIZER: String
val DEFAULT_ML_LEARN_DECAY: Double
val DEFAULT_ML_LEARN_RATE: Double
val DEFAULT_ML_LOSSFUNCTION_HUBER_DELTA: Double
val DEFAULT_ML_MATRIX_DOT_USE_PARALLEL_EXECUTOR: Boolean
val DEFAULT_ML_MINIBATCH_SIZE: Int
val DEFAULT_ML_MLR_RANK: Int
val DEFAULT_ML_MODEL_CLASS_NAME: String
val DEFAULT_ML_MODEL_IS_CLASSIFICATION: Boolean
val DEFAULT_ML_MODEL_SIZE: Int
val DEFAULT_ML_MODEL_TYPE: String
val DEFAULT_ML_NUM_CLASS: Int
val DEFAULT_ML_NUM_TREE: Int
val DEFAULT_ML_NUM_UPDATE_PER_EPOCH: Int
val DEFAULT_ML_OPTIMIZER: String
val DEFAULT_ML_OPT_DECAY_ALPHA: Double
val DEFAULT_ML_OPT_DECAY_BETA: Double
val DEFAULT_ML_OPT_DECAY_CLASS_NAME: String
val DEFAULT_ML_OPT_DECAY_INTERVALS: Int
val DEFAULT_ML_OPT_DECAY_ON_BATCH: Boolean
val DEFAULT_ML_RANK_NUM: Int
val DEFAULT_ML_REG_L1: Double
val DEFAULT_ML_REG_L2: Double
val DEFAULT_ML_ROBUSTREGRESSION_LOSS_DELTA: Double
val DEFAULT_ML_TREE_AGGRE_MAX_MEMORY_MB: Int
val DEFAULT_ML_TREE_CATEGORICAL_FEATURE: String
val DEFAULT_ML_TREE_FEATURE_SAMPLE_STRATEGY: String
val DEFAULT_ML_TREE_IMPURITY: String
val DEFAULT_ML_TREE_MAX_BIN: Int
val DEFAULT_ML_TREE_MAX_DEPTH: Int
val DEFAULT_ML_TREE_NODE_MIN_INFOGAIN: Int
val DEFAULT_ML_TREE_NODE_MIN_INSTANCE: Int
val DEFAULT_ML_TREE_SUB_SAMPLE_RATE: Int
val DEFAULT_ML_TREE_TASK_TYPE: String
val DEFAULT_ML_VALIDATE_RATIO: Double
val DEFAULT_ML_VERABLE_SAVE_WITHSLOT: Boolean
val KMEANS_C: String
val KMEANS_CENTER_NUM: String
val LOG_LIKELIHOOD: String
val ML_AUTO_TUNER_ITER: String
val ML_AUTO_TUNER_MINIMIZE: String
val ML_AUTO_TUNER_MODEL: String
val ML_AUTO_TUNER_PARAMS: String
val ML_BATCH_SAMPLE_RATIO: String
val ML_BLOCK_SIZE: String
val ML_DATA_HAS_LABEL: String
val ML_DATA_INPUT_FORMAT: String
val ML_DATA_LABEL_TRANS: String
val ML_DATA_LABEL_TRANS_THRESHOLD: String
val ML_DATA_POSNEG_RATIO: String
val ML_DATA_SPLITOR: String
val ML_DATA_USE_SHUFFLE: String
val ML_DECAY_INTERVALS: String
val ML_EMBEDDING_OPTIMIZER: String
val ML_EPOCH_NUM: String
val ML_FCLAYER_OPTIMIZER: String
val ML_FEATURE_INDEX_RANGE: String
val ML_FIELD_NUM: String
val ML_GBDT_BATCH_SIZE: String
val ML_GBDT_CATE_FEAT: String
val ML_GBDT_CLASS_NUM: String
val ML_GBDT_EVAL_METRIC: String
val ML_GBDT_FEATURE_SAMPLE_RATIO: String
val ML_GBDT_FULL_HESSIAN: String
val ML_GBDT_HIST_SUBTRACTION: String
val ML_GBDT_LIGHTER_CHILD_FIRST: String
val ML_GBDT_LOSS_FUNCTION: String
val ML_GBDT_MAX_LEAF_WEIGHT: String
val ML_GBDT_MAX_NODE_NUM: String
val ML_GBDT_MIN_CHILD_WEIGHT: String
val ML_GBDT_MIN_NODE_INSTANCE: String
val ML_GBDT_MIN_SPLIT_GAIN: String
val ML_GBDT_MULTI_CLASS_GRAD_CACHE: String
val ML_GBDT_MULTI_CLASS_STRATEGY: String
val ML_GBDT_PARALLEL_MODE: String
val ML_GBDT_REG_ALPHA: String
val ML_GBDT_REG_LAMBDA: String
val ML_GBDT_ROW_SAMPLE_RATIO: String
val ML_GBDT_SAMPLE_RATIO: String
val ML_GBDT_SERVER_SPLIT: String
val ML_GBDT_SPLIT_NUM: String
val ML_GBDT_TASK_TYPE: String
val ML_GBDT_THREAD_NUM: String
val ML_GBDT_TREE_DEPTH: String
val ML_GBDT_TREE_NUM: String
val ML_INPUTLAYER_OPTIMIZER: String
val ML_LEARN_DECAY: String
val ML_LEARN_RATE: String
val ML_LOSSFUNCTION_HUBER_DELTA: String
val ML_MATRIX_DOT_USE_PARALLEL_EXECUTOR: String

The predict error of all samples
val ML_MINIBATCH_SIZE: String
val ML_MLR_RANK: String
val ML_MODEL_CLASS_NAME: String
val ML_MODEL_IS_CLASSIFICATION: String
val ML_MODEL_SIZE: String
val ML_MODEL_TYPE: String
val ML_NUM_CLASS: String
val ML_NUM_TREE: String
val ML_NUM_UPDATE_PER_EPOCH: String
val ML_OPT_DECAY_ALPHA: String
val ML_OPT_DECAY_BETA: String
val ML_OPT_DECAY_CLASS_NAME: String
val ML_OPT_DECAY_INTERVALS: String
val ML_OPT_DECAY_ON_BATCH: String
val ML_RANK_NUM: String
val ML_REG_L1: String
val ML_REG_L2: String
val ML_ROBUSTREGRESSION_LOSS_DELTA: String
val ML_TREE_AGGRE_MAX_MEMORY_MB: String
val ML_TREE_CATEGORICAL_FEATURE: String
val ML_TREE_FEATURE_SAMPLE_STRATEGY: String
val ML_TREE_IMPURITY: String
val ML_TREE_MAX_BIN: String
val ML_TREE_MAX_DEPTH: String
val ML_TREE_NODE_MIN_INFOGAIN: String
val ML_TREE_NODE_MIN_INSTANCE: String
val ML_TREE_SUB_SAMPLE_RATE: String
val ML_TREE_TASK_TYPE: String
val ML_VALIDATE_RATIO: String
val ML_VERABLE_SAVE_WITHSLOT: String
val TRAIN_ERROR: String

The predict error of all samples
val TRAIN_LOSS: String

The loss sum of all samples
val VALID_ERROR: String
val VALID_LOSS: String
final def asInstanceOf[T0]: T0

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final def eq(arg0: AnyRef): Boolean

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def equals(arg0: Any): Boolean

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def finalize(): Unit

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final def getClass(): Class[_]

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def hashCode(): Int

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final def isInstanceOf[T0]: Boolean

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final def ne(arg0: AnyRef): Boolean

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final def notify(): Unit

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final def notifyAll(): Unit

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final def synchronized[T0](arg0: ⇒ T0): T0

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def toString(): String

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final def wait(): Unit

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final def wait(arg0: Long, arg1: Int): Unit

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final def wait(arg0: Long): Unit

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Related Doc: package conf

object AngelMLConf

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

val ANGEL_COMPRESS_BYTES: String

val ANGEL_ML_INC_TRAIN: String

val ANGEL_ML_PREDICT: String

val ANGEL_ML_TRAIN: String

val ANGEL_WORKER_THREAD_NUM: String

val DEFAULT_ANGEL_COMPRESS_BYTES: Int

val DEFAULT_ANGEL_WORKER_THREAD_NUM: Int

val DEFAULT_KMEANS_C: Double

val DEFAULT_KMEANS_CENTER_NUM: Int

val DEFAULT_ML_AUTO_TUNER_ITER: Int

val DEFAULT_ML_AUTO_TUNER_MINIMIZE: Boolean

val DEFAULT_ML_AUTO_TUNER_MODEL: String

val DEFAULT_ML_BATCH_SAMPLE_RATIO: Double

val DEFAULT_ML_BLOCK_SIZE: Int

val DEFAULT_ML_DATA_HAS_LABEL: Boolean

val DEFAULT_ML_DATA_INPUT_FORMAT: String

val DEFAULT_ML_DATA_LABEL_TRANS: String

val DEFAULT_ML_DATA_LABEL_TRANS_THRESHOLD: Int

val DEFAULT_ML_DATA_POSNEG_RATIO: Int

val DEFAULT_ML_DATA_SPLITOR: String

val DEFAULT_ML_DATA_USE_SHUFFLE: Boolean

val DEFAULT_ML_DECAY_INTERVALS: Int

val DEFAULT_ML_EMBEDDING_OPTIMIZER: String

val DEFAULT_ML_EPOCH_NUM: Int

val DEFAULT_ML_FCLAYER_OPTIMIZER: String

val DEFAULT_ML_FEATURE_INDEX_RANGE: Int

val DEFAULT_ML_FIELD_NUM: Int

val DEFAULT_ML_GBDT_BATCH_SIZE: Int

val DEFAULT_ML_GBDT_CATE_FEAT: String

val DEFAULT_ML_GBDT_CLASS_NUM: Int

val DEFAULT_ML_GBDT_EVAL_METRIC: String

val DEFAULT_ML_GBDT_FEATURE_SAMPLE_RATIO: Double

val DEFAULT_ML_GBDT_FULL_HESSIAN: Boolean

val DEFAULT_ML_GBDT_HIST_SUBTRACTION: Boolean

val DEFAULT_ML_GBDT_LIGHTER_CHILD_FIRST: Boolean

val DEFAULT_ML_GBDT_LOSS_FUNCTION: String

val DEFAULT_ML_GBDT_MAX_LEAF_WEIGHT: Double

val DEFAULT_ML_GBDT_MIN_CHILD_WEIGHT: Double

val DEFAULT_ML_GBDT_MIN_NODE_INSTANCE: Int

val DEFAULT_ML_GBDT_MIN_SPLIT_GAIN: Double

val DEFAULT_ML_GBDT_PARALLEL_MODE: String

val DEFAULT_ML_GBDT_REG_ALPHA: Int

val DEFAULT_ML_GBDT_REG_LAMBDA: Double

val DEFAULT_ML_GBDT_ROW_SAMPLE_RATIO: Int

val DEFAULT_ML_GBDT_SAMPLE_RATIO: Int

val DEFAULT_ML_GBDT_SERVER_SPLIT: Boolean

val DEFAULT_ML_GBDT_SPLIT_NUM: Int

val DEFAULT_ML_GBDT_TASK_TYPE: String

val DEFAULT_ML_GBDT_THREAD_NUM: Int

val DEFAULT_ML_GBDT_TREE_DEPTH: Int

val DEFAULT_ML_GBDT_TREE_NUM: Int

val DEFAULT_ML_INPUTLAYER_OPTIMIZER: String

val DEFAULT_ML_LEARN_DECAY: Double

val DEFAULT_ML_LEARN_RATE: Double

val DEFAULT_ML_LOSSFUNCTION_HUBER_DELTA: Double

val DEFAULT_ML_MATRIX_DOT_USE_PARALLEL_EXECUTOR: Boolean

val DEFAULT_ML_MINIBATCH_SIZE: Int

val DEFAULT_ML_MLR_RANK: Int

val DEFAULT_ML_MODEL_CLASS_NAME: String

val DEFAULT_ML_MODEL_IS_CLASSIFICATION: Boolean

val DEFAULT_ML_MODEL_SIZE: Int

val DEFAULT_ML_MODEL_TYPE: String

val DEFAULT_ML_NUM_CLASS: Int

val DEFAULT_ML_NUM_TREE: Int

val DEFAULT_ML_NUM_UPDATE_PER_EPOCH: Int

val DEFAULT_ML_OPTIMIZER: String

val DEFAULT_ML_OPT_DECAY_ALPHA: Double

val DEFAULT_ML_OPT_DECAY_BETA: Double

val DEFAULT_ML_OPT_DECAY_CLASS_NAME: String

val DEFAULT_ML_OPT_DECAY_INTERVALS: Int

val DEFAULT_ML_OPT_DECAY_ON_BATCH: Boolean

val DEFAULT_ML_RANK_NUM: Int

val DEFAULT_ML_REG_L1: Double