epub, mobi |eng | 2017-07-21 | Author:Pratap Dangeti

KNN classifier with breast cancer Wisconsin data example Breast cancer data has been utilized from the UCI machine learning repository http://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+%28Diagnostic%29 for illustration purposes. Here the task is to find ...

azw3 |eng | 2017-04-24 | Author:Giancarlo Zaccone & Md. Rezaul Karim & Ahmed Menshawy [Zaccone, Giancarlo]

def loss(pred, label): cross_entropy_loss = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits=pred, labels=label)) tf.summary.scalar('Entropy', cross_entropy_loss) reg_losses = tf.add_n(tf.get_collection("losses")) tf.scalar_summary('Reg_loss', reg_losses) return cross_entropy_loss + REGULARIZATION * reg_losses def train(loss, step): return tf.train.AdamOptimizer(LEARNING_RATE). minimize(loss, global_step=step) def get_next_batch(images, labels, ...

azw3 |eng | 2017-08-28 | Author:Ciaburro, Giuseppe [Ciaburro, Giuseppe]

Figure 5.5: Graphic description of the tree Figure 5.5 gives us useful information on the classification of the three floral species immediately. In most cases, the building of the decision ...

azw3 |eng | 2017-03-23 | Author:Dr. Param Jeet & Prashant Vats [Jeet, Dr. Param]

Figure 5.4: Normalized price series, difference, and trading signals The upper (ub) and lower bounds (lb) of the difference series can be calculated by adding and subtracting n times standard ...

azw3, mobi, epub |eng | 2015-04-07 | Author:Nielsen, Lars [Nielsen, Lars]

5 Artificial Intelligence, Machine Learning, and Deep Learning in Data Science “You can use all the quantitative data you can get, but you still have to distrust it and use ...

azw3 |eng | 2016-07-29 | Author:Zaccone, Giancarlo [Zaccone, Giancarlo]

Building the training set Import all the necessary libraries to our simulation: import matplotlib.pyplot as plt import numpy as np import tensorflow as tf import pandas as pd Note Pandas ...

azw3 |eng | 2017-07-31 | Author:Dan Van Boxel [Boxel, Dan Van]

So we know where to start let's look at the example image using the following code: # Let's take a look import matplotlib.pyplot as plt plt.ion() # Original plt.matshow(image[0]) plt.colorbar() ...

epub |eng | 2017-09-27 | Author:Bruno Joseph D'mello

AccountModel.find({ age: { $gt: 18, $lt: 30 } }, function(err, accounts) { console.log(accounts.length); // => 2 console.log(accounts[0].username); // => randomUser1 mongoose.connection.close(); }); Here, we use the standard MongoDB commands $gt ...

epub, pdf |eng | 2017-12-04 | Author:María Carina Roldán

epub |eng | 2016-11-14 | Author:Prateek Joshi & John Hearty & Bastiaan Sjardin & Luca Massaron & Alberto Boschetti

In this case, we're able to plot the results of a jitter test to easily identify whether a model has overfit. From a very strong initial position, an overfit model ...

epub |eng | 2015-11-07 | Author:Oz du Soleil

In the next figure, you see that the new Sold+Lost field shows up as an available entry in the field list. With Sold+Lost in the Values field, the total that’s ...

epub |eng | 2015-01-04 | Author:Helen Sun

Demand Forecast Demand forecast is another area where retailers are trying to better understand customers through the smart use of new data sources. As we discussed earlier in this chapter, ...

epub, pdf |eng | 2013-07-29 | Author:Foster Provost & Tom Fawcett

When working with a classifier that gives scores to instances, in some situations the classifier decisions should be very conservative, corresponding to the fact that the classifier should have high ...

azw3 |eng | 2017-08-31 | Author:Prabhanjan Narayanachar Tattar [Tattar, Prabhanjan Narayanachar]

Time for action – testing probability of success We will use the R function binom.test for testing hypotheses problems related to p. This function takes as arguments n number of ...

epub, pdf |eng | | Author:Thomas Mailund

Front: lazy_thunk( cons(1, cons(2, cons(3, nil))) ) Back: nil At this point, the entire back list has been reversed and appended to the front queue, and from here on we ...