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View SF-PCA.jl
using MultivariateStats # PCA
using PlotlyJS # データプロット用 Plotly.jl ではなく js実装を呼ぶ PlotlyJS.jl こちらの方がメンテされている
using CSV, DataFrames # CSV と DataFrames が扱えるように
df = CSV.File("SF.csv") |> DataFrame
reciprocals = 1 ./ Matrix(df[:,2:8]) # 逆数にして1番目の性格の値が大きくなるように
top5 = coalesce.(reciprocals, 0.0) # missing を zero で埋める
M = fit(PCA, top5; maxoutdim=2)
components = MultivariateStats.transform(M, top5) # 説明変数情報
projections = projection(M) # 主成分にProjection
View CADDi 2018 for Beginners C - Product and GCD code.ipynb
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View AtCoder Beginner Contest 115 D Christmas.ipynb
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View Hyperopt.jl
using Hyperopt
using DecisionTree
using MLDatasets
using Statistics
train_x, train_y = MNIST.traindata(Float32)
test_x, test_y = MNIST.testdata(Float32)
train_features = Array(transpose(MNIST.convert2features(train_x)))
test_features = Array(transpose(MNIST.convert2features(test_x)))
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View config.yml
version: 2
jobs:
build:
docker:
- image: circleci/ruby:2.5-node-browsers
environment:
RAILS_ENV: test
# https://circleci.com/docs/2.0/faq/#how-can-i-set-the-timezone-in-docker-images
TZ: "/usr/share/zoneinfo/Asia/Tokyo"
- image: circleci/postgres:10-alpine