bbengfort

package main

import (
	"context"
	"fmt"
	"log"
	"time"

	"github.com/BTrDB/btrdb"
	"github.com/PingThingsIO/smartgridstore/modules/creds"

bbengfort

from sklearn.model_selection import train_test_split as tts


def visualizer(
    model, 
    X_train, 
    y_train, 
    X_test=None, 
    y_test=None,
    ax=None, 

bbengfort

import os
import time
import btrdb

from tabulate import tabulate

db = btrdb.connect("api.research.predictivegrid.com:4411", "48BE21A7A13661B1EED5AB87")


def list_collection(prefix):

bbengfort

{% set name = "yellowbrick" %}
{% set version = "1.3" %}
{% set file_ext = "tar.gz" %}
{% set hash_type = "sha256" %}
{% set hash_value = "29eeedef78c2e5f37d05f558817b108108c34d72d37d0b05afdf969645b60ba1" %}

package:
  name: '{{ name|lower }}'
  version: '{{ version }}'

bbengfort

#!/usr/bin/env python

def hex2rgb(color):
    color = color.lstrip("#")
    return tuple(
        int(color[idx:idx+2], 16)
        for idx in (0, 2, 4)
    )

bbengfort

#!/usr/bin/env python3

"""
Visual reports for classification models using matplotlib and scikit-learn.
"""

import numpy as np
import matplotlib.pyplot as plt

from sklearn.model_selection import train_test_split as tts

bbengfort

import numpy as np
import matplotlib.pyplot as plt

def plot_classification_report(cr, title='Classification report ', with_avg_total=False, cmap=plt.cm.Blues):

    lines = cr.split('\n')

    classes = []
    plotMat = []
    for line in lines[2 : (len(lines) - 3)]:

bbengfort

#!/usr/bin/env python
# codehead
# Scans the local directory if it's a git repository and adds the ID line.
#
# Author:   Benjamin Bengfort <benjamin@bengfort.com>
# Created:  Mon Mar 07 17:53:36 2016 -0500
#
# Copyright (C) 2016 Bengfort.com
# For license information, see LICENSE.txt
#

bbengfort

import numpy as np
import matplotlib.pyplot as plt

from yellowbrick.datasets import load_credit

from sklearn.preprocessing import StandardScaler
from sklearn.decomposition import PCA

# Load data from yellowbrick.datasets
X, y = load_credit()

bbengfort

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as grid

from mpl_toolkits.axes_grid1 import make_axes_locatable, axes_size


def joint_plot(x, y, ax=None):
    """
    Create a square joint plot of x and y.