public Form_IBCF()
{
InitializeComponent();
this.comboBox1.Enabled = false;
obj_AssStrategy = new cAssStrategy();
this.comboBox2.Items.Clear();
for (int i = 15; i < cReadinData.test_usernum[comboBox1.SelectedIndex]; i++)
{
this.comboBox2.Items.Add(i);
}
dataGridView1.RowHeadersVisible = false;
// 初始化，最近邻居数量最大为200
obj_ItemBased_CF = new cItemBased_CF(200);
for (int i = 1; i <= 1682; i++)
{
obj_ItemBased_CF.generateItemNN(i);
}
// 读取最近邻项目及相似值文件，避免重复计算
obj_ItemBased_CF.readFile();
this.comboBox2.SelectedIndex = 0;
}
public Form_SlopeOne()
{
InitializeComponent();
// 默认选择第一个数据集
this.comboBox1.SelectedIndex = 0;
// 读取数据，得到训练用户集合以及测试用户集合
obj_ReadData = new cReadinData(this.comboBox1.SelectedIndex);
obj_AssStrategy = new cAssStrategy();
testUsers = cReadinData.getTestUser();
trainUsers = cReadinData.getBaseUser();
this.dataGridView1.RowHeadersVisible = false;
this.dataGridView2.RowHeadersVisible = false;
for (int i = 0; i < count_Num.Length; i++)
{
count_Num[i] = 0;
stat_Info[i] = 0;
}
// 根据选择的数据集，填充用户ID的下拉列表
for (int i = 0; i < testUsers.Length - 1; i++)
{
this.comboBox2.Items.Add(testUsers[i + 1].id);
}
// 用户ID默认选择第一个
this.comboBox2.SelectedIndex = 0;
obj_SlopeOne = new SlopeOne();
for (int i = 1; i < trainUsers.Length; i++)
{
userRating = new Dictionary <int, float>();
//count_Num[trainUsers[i].RatingNums/20]++;
for (int j = 1; j < trainUsers[i].Ratings.Length; j++)
{
if (trainUsers[i].Ratings[j] != 0)
{
userRating.Add(j, (float)trainUsers[i].Ratings[j]);
}
}
obj_SlopeOne.AddUserRatings(userRating);
}
this.comboBox3.Items.Clear();
// 填充 连续运行用户数目 下拉列表
for (int i = 15; i < testUsers.Length; i++)
{
comboBox3.Items.Add(i);
}
this.comboBox3.SelectedIndex = 0;
}
private void button1_Click(object sender, EventArgs e)
{
// 记录当前时间
int count_predit = 0;
DateTime dt_1 = DateTime.Now;
Rec_Items_num = int.Parse(this.textBox9.Text);
userRating = new Dictionary <int, float>();
// 得到用户
cUser testUser = testUsers[comboBox2.SelectedIndex + 1];
userid = testUser.id;
userRating = new Dictionary <int, float>();
for (int j = 1; j < trainUsers[userid].Ratings.Length; j++)
{
if (trainUsers[userid].Ratings[j] != 0)
{
userRating.Add(j, (float)trainUsers[userid].Ratings[j]);
}
}
// count_predit = trainUsers[userID].Ratings.Length - trainUsers[userID].RatingNums;
// 得到该用户的预测评分
IDictionary <int, float> Predictions = obj_SlopeOne.Predict(userRating);
obj_AssStrategy = obj_SlopeOne.getAssStrategy(userid, Predictions, Rec_Items_num, testUser);
DateTime dt_2 = DateTime.Now;
TimeSpan ts = dt_2.Subtract(dt_1);
this.textBox4.Text = obj_AssStrategy.MAE.ToString(); // MAE
this.textBox5.Text = ts.TotalMilliseconds + "ms"; // 时间
this.textBox6.Text = obj_AssStrategy.Precison.ToString(); // 查准率
this.textBox8.Text = obj_AssStrategy.Recall.ToString(); // 查全率
float F = obj_AssStrategy.calculateF_Measure(); // F1指标
this.textBox7.Text = F.ToString();
this.textBox2.Text = this.Rec_Items_num.ToString(); // Top-N 推荐数
this.textBox3.Text = "MAE:" + obj_AssStrategy.MAE + " 查准率:" + obj_AssStrategy.Precison + " 查全率:" +
obj_AssStrategy.Recall + " F值:" + F + " 总耗时:" + ts.TotalMilliseconds + "ms";
// this.dataGridView1.Rows.Add(count_dgv++, trainUsers[userIndex].id, this.Rec_Items_num, trainUsers[userIndex].RatingNums, obj_AssStrategy.MAE, obj_AssStrategy.Precison,
// obj_AssStrategy.Recall, F, ts.TotalMilliseconds + " ms");
Application.DoEvents();
stat_Info[trainUsers[userid].RatingNums / 50] += obj_AssStrategy.MAE;
count_Num[trainUsers[userid].RatingNums / 50]++;
// 累加相关数据
total_MAE += obj_AssStrategy.MAE;
total_Precison += obj_AssStrategy.Precison;
total_Recall += obj_AssStrategy.Recall;
total_F_Measure += F;
total_Time += ts.TotalMilliseconds;
}
private int Rec_Items_num; // Top-N 推荐项目数
public Form_UBCF()
{
InitializeComponent();
dataGridView1.RowHeadersVisible = false;
this.comboBox2.Items.Clear();
obj_AssStrategy = new cAssStrategy();
for (int i = 15; i < cReadinData.test_usernum[comboBox1.SelectedIndex]; i++)
{
this.comboBox2.Items.Add(i);
}
this.comboBox2.SelectedIndex = 0;
}
// 运行一次算法
private void button1_Click(object sender, EventArgs e)
{
// 记录当前时间
DateTime dt_1 = DateTime.Now;
this.Rec_Items_num = int.Parse(this.textBox13.Text); // Top-N推荐个数
this.progressBar1.Maximum = this.comboBox2.SelectedIndex + 15 + 22;
this.progressBar1.Value = 0;
// 读入数据，生成UI矩阵
this.textBox3.Text = "开始读入数据";
this.progressBar1.Value++;
Application.DoEvents();
cReadinData obj_ReadData = new cReadinData(comboBox1.SelectedIndex);
this.textBox3.Text = "读入数据完成 训练数据：" + obj_ReadData.sTrainFileName[comboBox1.SelectedIndex]
+ " 测试数据：" + obj_ReadData.testfileName[comboBox1.SelectedIndex];
this.progressBar1.Value++;
Application.DoEvents();
int number = int.Parse(textBox2.Text);
this.neigh_num = number;
// 相似度算法的选择
if (this.radioButton1.Checked)
{
sim_alg = 1;
}
else if (this.radioButton2.Checked)
{
sim_alg = 2;
}
else if (this.radioButton3.Checked)
{
sim_alg = 3;
}
// 测试用户数目，最少为15
testUserNum = this.comboBox2.SelectedIndex + 15;
this.textBox3.Text = "初始化最大邻居个数";
// 初始化，最近邻居数量最大为200
obj_ItemBased_CF = new cItemBased_CF(200);
this.progressBar1.Value++;
Application.DoEvents();
// 初始化相关数据
for (int i = 1; i <= 1682; i++)
{
this.textBox3.Text = "初始 " + i + " 个项目数据";
if ((i % 100) == 0)
{
this.progressBar1.Value++;
Application.DoEvents();
}
Application.DoEvents();
obj_ItemBased_CF.generateItemNN(i);
}
this.progressBar1.Value++;
Application.DoEvents();
this.textBox3.Text = "读取最近邻居及其相似值文件";
obj_ItemBased_CF.readFile();
this.progressBar1.Value++;
Application.DoEvents();
// 得到测试用户集合
cUser[] testUsers = cReadinData.getTestUser();
this.textBox3.Text = "读取测试用户集合";
this.progressBar1.Value++;
Application.DoEvents();
double MAE, Precison, Recall, F_Measure;
double total_MAE = 0, total_Precison = 0, total_Recall = 0, total_F_Measure = 0;
double average_MAE, average_Precison, average_Recall, average_F_Measure;
// for循环为每个测试用户产生预测评分以及Top-N推荐，并取得算法评价指标
for (int i = 1; i <= testUserNum; i++)
{
obj_AssStrategy = obj_ItemBased_CF.getPredictRating(testUsers[i], this.sim_alg, neigh_num, Rec_Items_num);
MAE = obj_AssStrategy.MAE;
Precison = obj_AssStrategy.Precison;
Recall = obj_AssStrategy.Recall;
F_Measure = obj_AssStrategy.calculateF_Measure();
// 累计各项指标的和
total_MAE += MAE;
total_Precison += Precison;
total_Recall += Recall;
total_F_Measure += F_Measure;
this.textBox3.Text = "第" + i.ToString() + "个用户 MAE:" + MAE.ToString() + " 查准率:" + Precison
+ " 查全率:" + Recall + " F值:" + F_Measure;
this.progressBar1.Value++;
Application.DoEvents();
}
// 计算各项指标的平均值
average_MAE = total_MAE / this.testUserNum;
average_Precison = total_Precison / this.testUserNum;
average_Recall = total_Recall / this.testUserNum;
average_F_Measure = total_F_Measure / this.testUserNum;
DateTime dt_2 = DateTime.Now;
TimeSpan ts = dt_2.Subtract(dt_1);
this.textBox3.Text = "完成 平均MAE:" + average_MAE.ToString() + " 平均查准率:" + average_Precison +
" 平均查全率:" + average_Recall + " 平均F值:" + average_F_Measure + " 总耗时:" + ts.TotalMilliseconds + "ms";
Application.DoEvents();
this.textBox4.Text = average_MAE.ToString();
this.textBox5.Text = ts.TotalMilliseconds + "ms";
this.textBox6.Text = this.sSimAlg[this.sim_alg - 1];
this.textBox7.Text = this.neigh_num.ToString();
this.textBox9.Text = average_Precison.ToString();
this.textBox10.Text = average_Recall.ToString();
this.textBox11.Text = average_F_Measure.ToString();
this.textBox12.Text = Rec_Items_num.ToString();
string log = this.sSimAlg[this.sim_alg - 1] + " 邻居数:" + this.neigh_num.ToString() + " 平均MAE:" +
average_MAE.ToString() + " 平均查准率:" + average_Precison + " 平均查全率:" + average_Recall +
" 平均F值:" + average_F_Measure + " 总耗时:" + ts.TotalMilliseconds + "ms";
this.dataGridView1.Rows.Add(count_dgv++, sSimAlg[sim_alg - 1], this.neigh_num, this.Rec_Items_num, average_MAE,
average_Precison, average_Recall, average_F_Measure, (ts.TotalMilliseconds / this.testUserNum) + " ms");
}
// 开始运行
private void button5_Click(object sender, EventArgs e)
{
int test_num = this.comboBox1.SelectedIndex + 15; // 测试用户数量
int N = int.Parse(this.textBox11.Text); // 推荐数目
cUser curTestUser; // 当前测试用户
cAssStrategy obj_AssStrategy = new cAssStrategy(); // 评价准则与指标
this.textBox7.Text = "测试用户数:" + test_num.ToString()
+ " Top-N 推荐数:" + N;
this.progressBar1.Maximum = (test_num - 1) * 3;; // 进度条最大值
this.progressBar1.Value = 0;
//////////////////////////////////////////////////////////////////////////
double total_N = 0, total_Precison = 0, total_Recall = 0, total_F = 0, total_Time = 0;
double Precison, Recall, F_Measure, Time;
DateTime dt_1, dt_2;
TimeSpan ts;
int real_RecNum = N;
// 对测试集中的用户开始产生推荐
int userid;
for (int i = 0; i < test_num - 1; i++)
{
curTestUser = testUsers[i + 1];
userid = curTestUser.id;
dt_1 = DateTime.Now; // 获取当前时间
// 得到ID为userid的用户所支持的关联规则集合
supp_AssRules[userid] = cApriori.getSupport_AssRules(userid);
this.textBox7.Text = "第 " + (i + 1) + " 个用户所支持的关联规则生成.";
this.progressBar1.Value++;
Application.DoEvents();
// 得到推荐电影列表
recItems[userid] = cApriori.getRecItems(supp_AssRules[userid], userid);
real_RecNum = (recItems[userid].Length > N ? N : recItems[userid].Length);
this.textBox7.Text = "第 " + (i + 1) + " 个用户的推荐列表生成.";
this.progressBar1.Value++;
Application.DoEvents();
// 评价准则与指标的计算
obj_AssStrategy = cApriori.getAssStrategy(curTestUser, N);
dt_2 = DateTime.Now;
ts = dt_2.Subtract(dt_1); // 时间间隔
Time = ts.TotalMilliseconds;
Precison = obj_AssStrategy.Precison;
Recall = obj_AssStrategy.Recall;
F_Measure = obj_AssStrategy.calculateF_Measure();
// this.label22.Text = userid.ToString(); // 用户ID
// this.label35.Text = real_RecNum.ToString(); // 实际推荐数目
total_N += real_RecNum;
this.label20.Text = Precison.ToString(); // 查准率
total_Precison += Precison;
this.label23.Text = Recall.ToString(); // 查全率
total_Recall += Recall;
this.label24.Text = F_Measure.ToString(); // F值
total_F += F_Measure;
this.label37.Text = Time + " ms"; // 算法运行时间
total_Time += Time;
this.textBox7.Text = "完成第 " + (i + 1) + " 个用户的结果分析.";
this.progressBar1.Value++;
Application.DoEvents();
}
// 计算平均值
int num = test_num - 1;
double average_N = ((double)total_N / (double)num);
double average_Precison = (double)((double)total_Precison / num);
double average_Recall = (double)((double)total_Recall / num);
double average_F = (double)((double)total_F / num);
double average_Time = (double)total_Time / num;
this.label29.Text = average_N.ToString();
this.label30.Text = average_Precison.ToString();
this.label31.Text = average_Recall.ToString();
this.label32.Text = average_F.ToString();
this.label33.Text = average_Time.ToString() + " ms";
Application.DoEvents();
}
private void button1_Click(object sender, EventArgs e)
{
DateTime dt_1 = DateTime.Now;
this.Rec_Items_num = int.Parse(this.textBox13.Text); // Top-N推荐个数
this.progressBar1.Maximum = (this.comboBox2.SelectedIndex + 15) * 10 + 5;
this.progressBar1.Value = 0;
// 读入数据，生成UI矩阵
this.textBox3.Text = "开始读入数据";
this.progressBar1.Value++;
Application.DoEvents();
cReadinData obj_ReadData = new cReadinData(comboBox1.SelectedIndex);
this.textBox3.Text = "读入数据完成 训练数据：" + obj_ReadData.sTrainFileName[comboBox1.SelectedIndex]
+ " 测试数据：" + obj_ReadData.testfileName[comboBox1.SelectedIndex];
this.progressBar1.Value += 2;
Application.DoEvents();
// 读取最近邻居个数
int number = int.Parse(textBox2.Text);
this.neigh_num = number;
// 相似度算法的选择
if (this.radioButton1.Checked)
{
sim_alg = 1;
}
else if (this.radioButton2.Checked)
{
sim_alg = 2;
}
else if (this.radioButton3.Checked)
{
sim_alg = 3;
}
// 测试用户数目，最少为15
testUserNum = this.comboBox2.SelectedIndex + 15;
cUserBased_CF obj_UserBased_CF = new cUserBased_CF(this.neigh_num);
cUser[] testUsers = cReadinData.getTestUser();
this.textBox3.Text = "初始化完成 相似度算法:" + sim_alg.ToString() +
" 最近邻居个数:" + this.neigh_num.ToString() + " 测试用户数:" + testUserNum.ToString();
this.progressBar1.Value += 2;
Application.DoEvents();
double MAE_1, Precison, Recall, F_Measure;
double total_MAE = 0, total_Precison = 0, total_Recall = 0, total_F_Measure = 0;
double average_MAE, average_Precison, average_Recall, average_F_Measure;
for (int i = 1; i <= this.testUserNum; i++)
{
this.progressBar1.Value += 5;
obj_AssStrategy = obj_UserBased_CF.getPredictRating(testUsers[i], this.sim_alg, Rec_Items_num);
// 取得各项算法评价指标
MAE_1 = obj_AssStrategy.MAE;
Precison = obj_AssStrategy.Precison;
Recall = obj_AssStrategy.Recall;
F_Measure = obj_AssStrategy.calculateF_Measure();
// 累计各项指标的和
total_MAE += MAE_1;
total_Precison += Precison;
total_Recall += Recall;
total_F_Measure += F_Measure;
this.textBox3.Text = "第 " + i.ToString() + " 个用户计算完成.";
this.progressBar1.Value += 5;
Application.DoEvents();
}
// 计算各个评价准则的平均值
average_MAE = total_MAE / this.testUserNum;
average_Precison = total_Precison / this.testUserNum;
average_Recall = total_Recall / this.testUserNum;
average_F_Measure = total_F_Measure / this.testUserNum;
DateTime dt_2 = DateTime.Now;
TimeSpan ts = dt_2.Subtract(dt_1);
this.textBox3.Text = "所有用户计算完成 总耗时:" + ts.TotalMilliseconds + " ms";
Application.DoEvents();
this.textBox4.Text = average_MAE.ToString();
this.textBox5.Text = ts.TotalMilliseconds + " ms";
this.textBox6.Text = this.sSimAlg[this.sim_alg - 1];
this.textBox7.Text = this.neigh_num.ToString();
this.textBox9.Text = average_Precison.ToString();
this.textBox10.Text = average_Recall.ToString();
this.textBox11.Text = average_F_Measure.ToString();
this.textBox12.Text = "20";
this.dataGridView1.Rows.Add(count_dgv++, sSimAlg[sim_alg - 1], this.neigh_num, this.Rec_Items_num, average_MAE,
average_Precison, average_Recall, average_F_Measure, (ts.TotalMilliseconds / this.testUserNum) + " ms");
}
// 对当前用户产生Top-N推荐
private void button2_Click(object sender, EventArgs e)
{
// 得到ID为userid的用户所支持的关联规则集合
supp_AssRules[userid] = cApriori.getSupport_AssRules(userid);
// 得到推荐电影列表
recItems[userid] = cApriori.getRecItems(supp_AssRules[userid], userid);
int n = int.Parse(this.textBox3.Text); // 得到推荐数目
// 所要求的推荐数目大于所能推荐的
if (n >= recItems[userid].Length)
{
n = recItems[userid].Length - 1;
}
this.dataGridView3.Rows.Clear();
int itemid;
// 填充推荐列表
string sGenres;
for (int i = 1; i <= n; i++)
{
itemid = recItems[userid][i].recItems_id;
sGenres = "";
for (int count_gen = 0; count_gen < objs_movieInfo[itemid].genres.Length; count_gen++)
{
// 形成影片类型字符串
if (objs_movieInfo[itemid].genres[count_gen] != "")
{
sGenres += objs_movieInfo[itemid].genres[count_gen] + " /";
}
}
if (sGenres != "")
{
sGenres = sGenres.Substring(0, sGenres.Length - 1);
}
this.dataGridView3.Rows.Add(i, recItems[userid][i].rec_Degree, objs_movieInfo[itemid].name,
objs_movieInfo[itemid].ReleaseDate, sGenres);
}
// 结果分析
// 得到测试用户在测试集中的索引
int testIndex = this.comboBox1.SelectedIndex + 1;
cUser currentTestUser = this.testUsers[testIndex];
this.label_test_total.Text = currentTestUser.RatingNums.ToString();
this.label_test_love.Text = currentTestUser.love_items_num.ToString();
this.label_test_dislove.Text = (currentTestUser.RatingNums - currentTestUser.love_items_num).ToString();
// 评价准则与指标
cAssStrategy obj_AssStrategy = cApriori.getAssStrategy(currentTestUser, n);
this.label_Prec.Text = obj_AssStrategy.Precison.ToString();
this.label_Reca.Text = obj_AssStrategy.Recall.ToString();
this.label_F_value.Text = obj_AssStrategy.calculateF_Measure().ToString();
// 推荐项目在测试集中的信息
ArrayList loveItems = cApriori.TestUserLoveItems_id;
ArrayList dratItems = cApriori.TestUserDratItems_id;
ArrayList unRatingItems = cApriori.TestUserUnRatingItems_id;
string sLoveIDs = "", sDratIDs = "", sUnRatingIDs = "";
// 喜欢的推荐项目ID
foreach (int value in loveItems)
{
sLoveIDs += value + " | ";
}
// 不喜欢的推荐项目ID
foreach (int value in dratItems)
{
sDratIDs += value + " | ";
}
// 未评价的推荐项目ID
foreach (int value in unRatingItems)
{
sUnRatingIDs += value + " | ";
}
this.label_loveid.Text = sLoveIDs.ToString();
this.label_disloveid.Text = sDratIDs.ToString();
this.label_unrating_id.Text = sUnRatingIDs.ToString();
}
