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3.0.0

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@andrewdalpino andrewdalpino released this 08 Oct 18:03
· 13 commits to master since this release
3.0.0
8eeb99f
  • Integers are now considered a categorical data type
  • Updated to Tensor API version 4.1
  • K Nearest Neighbors and KNN Regressor inference is now parallelized
  • Isolation Forest training and inference is now parallelized
  • Added disk-based streaming neural network snapshotting
  • Added validation interval parameter to MLPs and GBM Learners
  • Cross Entropy loss function now split into Binary and Multiclass
  • Logistic Regression, Softmax, and Adaline now use hold out set
  • Adaboost now uses validation set with early stopping window
  • Renamed TF-IDF dampening parameter to sublinear
  • Exportable Extractors now append by default with option to overwrite
  • RBX Serializer tracks major library version number, not minor
  • Added Class/Cluster Purity clustering metrics
  • V-measure, Completeness, and Homogeneity now use entropy-based formula
  • Fixed KDTree edge pruning + optimize traversal
  • Ball and Vantage Trees now require Subadditive kernels
  • K-d Trees now require Monotonic distance kernels
  • Optimize Dataset sort(), sorting is now unstable
  • Added per-class smoothing to Gaussian Naive Bayes
  • Added per-cluster smoothing to Gaussian Mixture
  • You can now exclude certain categories from one-hot encoding
  • Fixed SVC save/load using class map sidecar
  • Parallel Backends now default to max physical cores not logical
  • Added workers() method to the Backend interface
  • No longer save/load Backend state, transient per environment
  • Added Float Type Converter numeric string and ints to float
  • Boolean Converter now converts truthy and falsy
  • Interval Discretizer now encodes values as integers
  • Polynomial Expander now limited to 10'th degree
  • Updated to PSR-3 Log version 3
  • Update Amp Backend to Amp version 2.0
  • Removed Word Stemmer tokenizer
  • Removed window early stopping from TSNE
  • Removed output layer L2 Penalty parameter from MLP Learners
  • RBX serializer now emits warning on class revision mismatch
  • Class revision hash now compensates for circular references
  • Filesystem Persister now does atomic writes
  • Added cleanup() method to remove neural network residual state
  • Murmur3 new default Token Hashing Vectorizer hash function
  • Dataset fold() now distributes excess samples over all folds
  • Increase default Decision Tree max leaf node size from 3 to 5
  • Canonicalized He initializer
  • Xavier 2 now extends He as a deprecated alias
  • Remove Softmax activation function
  • Fix Multiclass layer gradient for non-Cross Entropy losses
  • Optimizers now take a Scheduler rather than a raw learning rate
  • MLP Learners now have gradient accumulation and clipping
  • MLP Learners can now freeze first k layers for fine-tuning
  • PlusPlus and KMC2 Seeders always return unique seeds
  • KMeans and Fuzzy C Means now restrict non-Euclidean kernels
  • NDJSON exporter now preserves zero decimal numbers as floats
  • Add Dataset chunked() factory for online training
  • Added L1 penalty to Dense layers
  • Adaline, Logistic Regression, Softmax Classifier now elastic net
  • Added Iterative interface with progress() method
  • Iterative Learners renamed steps() method to progress()
  • Changed default gradient-based minChange from 1e-4 to 1e-5
  • Prior is now default Strategy of Missing Data Imputer
  • DBSCAN is now a Learner, Probabilistic and Persistable
  • Grid Search now has a fromNamedParams() factory method
  • Grid Search now generates a results() table
  • Can now disable windowed early-stopping completely with window = 0
  • TSNE now has KL Divergence loss evaluation and early stopping
  • Added binnedSplit(), binnedFold(), and stratifyByLabelBins()
  • stratifiedSplit() and stratifiedFold() now throw on continuous labels
  • Validators and regressors now stratify continuous labels by bin
  • Image Rotator offset is now optional and default jitter is 0.2
  • Added fillColor parameter to Image Rotator
  • Remove holdOut paramereter from Learners with validation set
  • Added setValidationDataset() method to Learners with validation set
  • Pipeline is now a Transformer decorator
  • Added PersistentTransformer decorator
  • Removed Trainable interface, API transferred to Learner interface
  • GridSearch now has a setup() hook before each iteration
  • GELU now uses exact formula instead of the tanh approximation
  • Fix TruncatedSVD lossiness value
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