Semagle.Framework
Semagle.Algorithms Namespace
Semagle.Data.Formats Namespace
| Module | Description |
| LibSVM |
Reading and writing LIBSVM files |
Semagle.Logging Namespace
| Type | Description |
| EpochNanoSeconds |
The # of nanoseconds after 1970-01-01 00:00:00. |
| Gauge | |
| LiterateConsoleTarget |
Logs a line in a format that is great for human consumption, using console colours to enhance readability. Sample: [10:30:49 INF] User "AdamC" began the "checkout" process with 100 cart items |
| LogLevel |
The log level denotes how 'important' the gauge or event message is. |
| LoggerBuilder | |
| LoggingConfig | |
| Message |
This is record that is logged. It's capable of representing both metrics (gauges) and events. See https://github.com/logary/logary for details. |
| OutputWindowTarget | |
| StacktraceLineData | |
| StopwatchTicks | |
| TextWriterTarget | |
| Units | |
| Value |
Allows you to clearly deliniate the accuracy and type of the measurement/gauge. |
| Module | Description |
| Constants |
Time calculation constants |
| DateTimeOffset | |
| DateTimeOffsetEx | |
| Global | |
| Literals |
Module that contains the 'known' keys of the Maps in the Message type's context. |
| Literate | |
| Log |
Module for acquiring static loggers (when you don't want or can't) pass loggers as values. |
| Message |
The Message module contains functions that can help callers compose messages. This module is especially helpful to open to make calls into Logary's facade small. |
| StopwatchTicks | |
| Targets |
"Shortcut" for creating targets; useful at the top-level configuration point of your library. |
Semagle.MachineLearning.Metrics Namespace
| Module | Description |
| Classification |
Classification metrics |
| Regression |
Regression metrics |
Semagle.MachineLearning.SSVM Namespace
| Type | Description |
| Argmax<'Y> |
Argmax function result |
| ArgmaxFunction<'Y> |
Argmax function type |
| FeatureFunction<'X> |
Simple feature function |
| JointFeatureFunction<'X, 'Y> |
Joint feature function type |
| JointKernel<'X, 'Y> |
Joint kernel function type |
| LossFunction<'Y> |
Structured SVM loss function type |
| MultiClass<'X, 'Y> |
Structured SVM model for multi-class classification |
| Rescaling |
Structured SVM rescaling |
| Module | Description |
| LRF | |
| MultiClass | |
| OneSlack |
Semagle.MachineLearning.SVM Namespace
| Type | Description |
| Kernel<'X> |
Kernel function |
| SVM<'X, 'Y> |
SVM model definition includes kernel function, array of support vectors with respective weights and bias value. |
| Module | Description |
| Kernel |
Popular kernel functions definitions |
| LRU | |
| MultiClass |
Multi-class classification |
| OneClass |
One class classification (distribution estimation) |
| Regression |
Regression |
| SMO |
Implementation of Sequential Minimal Optimization (SMO) algorithm |
| SVM | |
| TwoClass |
Two class classification |
Semagle.Numerics.Vectors Namespace
| Type | Description |
| DenseVector |
Dense vector stores both zero and non-zero values |
| SparseVector |
Sparse vector stores non-zero values and non-zero values indices |
| Vector |
Vector abstract class |
