toshihikoyanase

mkdir tmp
for f in *b.zip
do 
    echo $f
    pushd tmp
    unzip ../$f
    popd
done

mkdir utf8

toshihikoyanase

#! /usr/bin/env python
# -*- coding: utf-8 -*-
import argparse


def run():
    args = parse_args()
    print("Input path: {0}".format(args.input_path))

toshihikoyanase

#!/usr/bin/env python
import tweepy
import datetime
import time
# See http://blog.unfindable.net/archives/4257                                                        

locationsL=[-180,-90,180,90]

class StreamListener(tweepy.StreamListener):
    def __init__(self, api=None):

toshihikoyanase

"""
Optuna example that optimizes a simple quadratic function.

In this example, we demonstrate how to import existing experimental results 
and continue the optimization.

We have the following two ways to execute this example:

(1) Execute this code directly.
    $ python quadratic_trial_import.py

toshihikoyanase

"""
Optuna example that optimizes a simple quadratic function.

In this example, we demonstrate how to import existing experimental results
and continue the optimization.

We have the following two ways to execute this example:

(1) Execute this code directly.
    $ python quadratic_change_range.py

toshihikoyanase

toshihikoyanase

Settings: (sigopt/evalset/auc-test-suites)

• Problems: 38
• Metrics: best

Solver	Borda	Firsts
(a) optuna#tpe-faster	0	37
(b) optuna#tpe-latest	1	38

Plot of best value

toshihikoyanase

import ...

def objective(trial):
    ...
    alpha = trial.suggest_loguniform('alpha', 1e-5, 1e-1)
    clf = sklearn.linear_model.SGDClassifier(alpha=alpha)

    for step in range(100):
        clf.partial_fit(train_x, train_y, classes=classes)

toshihikoyanase

import math
import sklearn.datasets
import sklearn.linear_model
import sklearn.model_selection

import optuna


class NaNValuePruner(optuna.pruners.BasePruner):

toshihikoyanase

"""
Optuna example that optimizes a classifier configuration for cancer dataset using LightGBM tuner.

In this example, we optimize the validation log loss of cancer detection.

You can execute this code directly.
    $ python lightgbm_tuner_parallel.py [-p]

"""
import argparse