release 0.1.2

Author: kortirso

.DS_Store

@@ -4,11 +4,15 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
 and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.html).
 
-## [Unreleased]
+## [0.1.2] - 2018-11-22
 ### Added
 - CHANGELOG.md file
 - Add simple Linear Regression predictor
 
+### Modified
+- Readme
+- Tests
+
 ## [0.1.1] - 2018-11-19
 ### Added
 - Gaussian Naive Bayes algorithm

CHANGELOG.md

@@ -19,7 +19,7 @@ by adding `learn_kit` to your list of dependencies in `mix.exs`:
 ```elixir
 def deps do
   [
-    {:learn_kit, "~> 0.1.1"}
+    {:learn_kit, "~> 0.1.2"}
   ]
 end
 ```

README.md

@@ -24,7 +24,7 @@ defmodule LearnKit.Knn do
       %LearnKit.Knn{data_set: []}
 
   """
-  @spec new() :: %LearnKit.Knn{data_set: []}
+  @spec new() :: %Knn{data_set: []}
 
   def new do
     []
@@ -44,7 +44,7 @@ defmodule LearnKit.Knn do
       %LearnKit.Knn{data_set: [a1: [[1, 2], [2, 3]], b1: [[-1, -2]]]}
 
   """
-  @spec new(data_set) :: %LearnKit.Knn{data_set: data_set}
+  @spec new(data_set) :: %Knn{data_set: data_set}
 
   def new(data_set) do
     %Knn{data_set: data_set}
@@ -60,11 +60,11 @@ defmodule LearnKit.Knn do
 
   ## Examples
 
-      iex> classificator |> LearnKit.Knn.add_train_data({:a1, [-1, -1]})
+      iex> classificator = classificator |> LearnKit.Knn.add_train_data({:a1, [-1, -1]})
       %LearnKit.Knn{data_set: [a1: [[-1, -1]]]}
 
   """
-  @spec add_train_data(%LearnKit.Knn{data_set: data_set}, point) :: %LearnKit.Knn{data_set: data_set}
+  @spec add_train_data(%Knn{data_set: data_set}, point) :: %Knn{data_set: data_set}
 
   def add_train_data(%Knn{data_set: data_set}, {key, value}) do
     features = if Keyword.has_key?(data_set, key), do: Keyword.get(data_set, key), else: []
@@ -93,7 +93,7 @@ defmodule LearnKit.Knn do
       {:ok, :a1}
 
   """
-  @spec classify(%LearnKit.Knn{data_set: data_set}, [tuple]) :: {:ok, label}
+  @spec classify(%Knn{data_set: data_set}, [tuple]) :: {:ok, label}
 
   def classify(%Knn{data_set: data_set}, options \\ []) do
     try do

lib/learn_kit/knn.ex

@@ -31,7 +31,7 @@ defmodule LearnKit.NaiveBayes.Gaussian do
       %LearnKit.NaiveBayes.Gaussian{data_set: [], fit_data: []}
 
   """
-  @spec new() :: %LearnKit.NaiveBayes.Gaussian{data_set: []}
+  @spec new() :: %Gaussian{data_set: []}
 
   def new do
     []
@@ -51,7 +51,7 @@ defmodule LearnKit.NaiveBayes.Gaussian do
       %LearnKit.NaiveBayes.Gaussian{data_set: [a1: [[1, 2], [2, 3]], b1: [[-1, -2]]], fit_data: []}
 
   """
-  @spec new(data_set) :: %LearnKit.NaiveBayes.Gaussian{data_set: data_set}
+  @spec new(data_set) :: %Gaussian{data_set: data_set}
 
   def new(data_set) do
     %Gaussian{data_set: data_set}
@@ -67,11 +67,11 @@ defmodule LearnKit.NaiveBayes.Gaussian do
 
   ## Examples
 
-      iex> classificator |> LearnKit.NaiveBayes.Gaussian.add_train_data({:a1, [-1, -1]})
+      iex> classificator = classificator |> LearnKit.NaiveBayes.Gaussian.add_train_data({:a1, [-1, -1]})
       %LearnKit.NaiveBayes.Gaussian{data_set: [a1: [[-1, -1]]], fit_data: []}
 
   """
-  @spec add_train_data(%LearnKit.NaiveBayes.Gaussian{data_set: data_set}, point) :: %LearnKit.NaiveBayes.Gaussian{data_set: data_set}
+  @spec add_train_data(%Gaussian{data_set: data_set}, point) :: %Gaussian{data_set: data_set}
 
   def add_train_data(%Gaussian{data_set: data_set}, {key, value}) do
     features = if Keyword.has_key?(data_set, key), do: Keyword.get(data_set, key), else: []
@@ -88,7 +88,7 @@ defmodule LearnKit.NaiveBayes.Gaussian do
 
   ## Examples
 
-      iex> classificator |> LearnKit.NaiveBayes.Gaussian.fit
+      iex> classificator = classificator |> LearnKit.NaiveBayes.Gaussian.fit
       %LearnKit.NaiveBayes.Gaussian{
         data_set: [a1: [[-1, -1]]],
         fit_data: [
@@ -100,7 +100,7 @@ defmodule LearnKit.NaiveBayes.Gaussian do
       }
 
   """
-  @spec fit(%LearnKit.NaiveBayes.Gaussian{data_set: data_set}) :: %LearnKit.NaiveBayes.Gaussian{data_set: data_set, fit_data: fit_data}
+  @spec fit(%Gaussian{data_set: data_set}) :: %Gaussian{data_set: data_set, fit_data: fit_data}
 
   def fit(%Gaussian{data_set: data_set}) do
     %Gaussian{data_set: data_set, fit_data: fit_data(data_set)}
@@ -119,7 +119,7 @@ defmodule LearnKit.NaiveBayes.Gaussian do
       {:ok, [a1: 0.0359, a2: 0.0039]}
 
   """
-  @spec predict_proba(%LearnKit.NaiveBayes.Gaussian{fit_data: fit_data}, feature) :: {:ok, predictions}
+  @spec predict_proba(%Gaussian{fit_data: fit_data}, feature) :: {:ok, predictions}
 
   def predict_proba(%Gaussian{fit_data: fit_data}, feature) do
     result = fit_data |> classify_data(feature)
@@ -139,7 +139,7 @@ defmodule LearnKit.NaiveBayes.Gaussian do
       {:ok, {:a1, 0.334545454}}
 
   """
-  @spec predict(%LearnKit.NaiveBayes.Gaussian{fit_data: fit_data}, feature) :: {:ok, prediction}
+  @spec predict(%Gaussian{fit_data: fit_data}, feature) :: {:ok, prediction}
 
   def predict(%Gaussian{fit_data: fit_data}, feature) do
     result = fit_data |> classify_data(feature) |> Enum.sort_by(&(elem(&1, 1))) |> Enum.at(-1)
@@ -159,7 +159,7 @@ defmodule LearnKit.NaiveBayes.Gaussian do
       {:ok, 0.857143}
 
   """
-  @spec score(%LearnKit.NaiveBayes.Gaussian{data_set: data_set, fit_data: fit_data}) :: {:ok, number}
+  @spec score(%Gaussian{data_set: data_set, fit_data: fit_data}) :: {:ok, number}
 
   def score(%Gaussian{data_set: data_set, fit_data: fit_data}) do
     result = fit_data |> calc_score(data_set)

lib/learn_kit/naive_bayes/gaussian.ex

@@ -23,7 +23,7 @@ defmodule LearnKit.Regression.Linear do
       %LearnKit.Regression.Linear{factors: [], results: [], coefficients: []}
 
   """
-  @spec new() :: %LearnKit.Regression.Linear{factors: [], results: [], coefficients: []}
+  @spec new() :: %Linear{factors: [], results: [], coefficients: []}
 
   def new do
     Linear.new([], [])
@@ -43,7 +43,7 @@ defmodule LearnKit.Regression.Linear do
       %LearnKit.Regression.Linear{factors: [1, 2, 3, 4], results: [3, 6, 10, 15], coefficients: []}
 
   """
-  @spec new(factors, results) :: %LearnKit.Regression.Linear{factors: factors, results: results, coefficients: []}
+  @spec new(factors, results) :: %Linear{factors: factors, results: results, coefficients: []}
 
   def new(factors, results) do
     %Linear{factors: factors, results: results}
@@ -66,7 +66,7 @@ defmodule LearnKit.Regression.Linear do
       }
 
   """
-  @spec fit(%LearnKit.Regression.Linear{factors: factors, results: results}) :: %LearnKit.Regression.Linear{factors: factors, results: results, coefficients: coefficients}
+  @spec fit(%Linear{factors: factors, results: results}) :: %Linear{factors: factors, results: results, coefficients: coefficients}
 
   def fit(%Linear{factors: factors, results: results}) do
     %Linear{factors: factors, results: results, coefficients: fit_data(factors, results)}
@@ -86,7 +86,7 @@ defmodule LearnKit.Regression.Linear do
       {:ok, [14.5, 30.5, 50.5]}
 
   """
-  @spec predict(%LearnKit.Regression.Linear{coefficients: coefficients}, list) :: {:ok, list}
+  @spec predict(%Linear{coefficients: coefficients}, list) :: {:ok, list}
 
   def predict(%Linear{coefficients: coefficients}, samples) do
     result = samples |> Enum.map(fn sample -> predict_sample(sample, coefficients) end)
@@ -106,7 +106,7 @@ defmodule LearnKit.Regression.Linear do
       {:ok, 0.9876543209876543}
 
   """
-  @spec score(%LearnKit.Regression.Linear{factors: factors, results: results, coefficients: coefficients}) :: {:ok, number}
+  @spec score(%Linear{factors: factors, results: results, coefficients: coefficients}) :: {:ok, number}
 
   def score(%Linear{factors: factors, results: results, coefficients: coefficients}) do
     {:ok, calculate_score(coefficients, factors, results)}

lib/learn_kit/regression/linear.ex

@@ -8,7 +8,7 @@ defmodule LearnKit.MixProject do
   def project do
     [
       app: :learn_kit,
-      version: "0.1.1",
+      version: "0.1.2",
       elixir: "~> 1.7",
       name: "LearnKit",
       description: @description,