摘要：
Out: n_digits: 10, n_samples 1797, n_features 64 __________________________________________________________________________________ init time inertia 阅读全文
摘要：
def get_model(input_dim=33): # Build neural network net = tflearn.input_data(shape=[None, input_dim]) net = batch_normalization(net) #net = tflearn.fu 阅读全文
摘要：
How to handle Imbalanced Classification Problems in machine learning? from:https://www.analyticsvidhya.com/blog/2017/03/imbalanced-classification-prob 阅读全文
摘要：
Using SMOTEBoost and RUSBoost to deal with class imbalance from:https://aitopics.org/doc/news:1B9F7A99/ Binary classification with strong class imbala 阅读全文
摘要：
from sklearn.ensemble import RandomForestClassifier import matplotlib.pyplot as plt selected_feat_names=set() for i in range(10): #这里我们进行十次循环取交集 tmp = 阅读全文
摘要：
MLP 64,2 preprocessing.MinMaxScaler().fit(X) test confusion_matrix:[[129293 2734] [ 958 23375]] precision recall f1-score support 0 0.99 0.98 0.99 132 阅读全文
摘要：
demo代码： extend data 表示待预测的数据 关于mic： 阅读全文