Kaggle Regression

Remix this to get started with Clojure and add-lib.

{:deps
  { org.clojure/clojure {:mvn/version "1.9.0"}
    org.clojure/tools.deps.alpha {
      :git/url "https://github.com/clojure/tools.deps.alpha.git"
      :sha "f6c080bd0049211021ea59e516d1785b08302515"}}}

deps.edn

You can add dependencies by modifying the deps.edn above (requires a runtime restart)...

(use 'clojure.tools.deps.alpha.repl)
(clojure-version)

3.9s

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"1.9.0"

...or at runtime using add-lib:

(add-lib 'metasoarous/oz {:mvn/version "1.5.2"})

103.1s

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true

(add-lib 'techascent/tech.ml {:mvn/version "0.19"})

44.4s

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true

wget https://raw.githubusercontent.com/gigasquid/mxnet-gan-flan/master/pre-trained/model-g-symbol.json

1.0s

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ls

0.7s

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(require '[tech.ml.dataset.etl :as etl])
(require '[tech.ml.dataset.etl.pipeline-operators :as pipe-ops])
(require '[tech.ml.dataset.etl.math-ops :as pipe-math]) 
(require '[tech.ml.dataset.etl.column-filters :as col-filters]) 
(require '[tech.ml.dataset :as dataset]) 
(require '[tech.ml.dataset.column :as ds-col])
(require '[tech.ml :as ml]) 
(require '[tech.ml.loss :as loss])
(require '[tech.ml.utils :as ml-utils])
(require '[clojure.core.matrix :as m]) 
;;use tablesaw as dataset backing store 
(require '[tech.libs.tablesaw :as tablesaw]) 
;;model generators 
(require '[tech.libs.xgboost]) 
;(require '[tech.libs.smile.regression])
(require '[tech.libs.svm]) 
;;put/get nippy
(require '[tech.io :as io])
(require '[clojure.pprint :as pp])
(require '[clojure.set :as c-set]) 
(import '[java.io File])

0.6s

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