class TensorflowSentiment extends Serializable with Logging
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Instance Constructors
- new TensorflowSentiment(tensorflow: TensorflowWrapper, encoder: ClassifierDatasetEncoder, verboseLevel: nlp.annotators.ner.Verbose.Value)
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final
def
!=(arg0: Any): Boolean
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- val encoder: ClassifierDatasetEncoder
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final
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getClass(): Class[_]
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def
getLogName: String
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def
hashCode(): Int
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- def internalPredict(inputs: Array[Array[Float]], configProtoBytes: Option[Array[Byte]] = None): Array[Int]
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val
logger: Logger
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- def measure(labeled: Array[(Array[Float], Array[Int])], batchSize: Int = 100): Float
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notifyAll(): Unit
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def
outputLog(value: ⇒ String, uuid: String, shouldLog: Boolean, outputLogsPath: String): Unit
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- def predict(docs: Seq[(Int, Seq[Annotation])], configProtoBytes: Option[Array[Byte]] = None, threshold: Float = 0.6f, thresholdLabel: String = "neutral"): Seq[Annotation]
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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- val tensorflow: TensorflowWrapper
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def
toString(): String
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- def train(inputs: Array[Array[Float]], labels: Array[String], lr: Float = 5e-3f, batchSize: Int = 64, dropout: Float = 0.5f, startEpoch: Int = 0, endEpoch: Int = 10, configProtoBytes: Option[Array[Byte]] = None, validationSplit: Float = 0.0f, enableOutputLogs: Boolean = false, outputLogsPath: String, uuid: String = ...): Unit
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val
verboseLevel: nlp.annotators.ner.Verbose.Value
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- TensorflowSentiment → Logging
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final
def
wait(): Unit
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def
wait(arg0: Long, arg1: Int): Unit
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wait(arg0: Long): Unit
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