public LinearCoef GetDataArgsByFile()
{
string lines = File.ReadAllText(@"d:\linear_coef2.json");
LinearCoef linearCoef = new LinearCoef();
var dd = JsonConvert.DeserializeObject<LinearCoef>(lines);
linearCoef.ListCoef = dd.ListCoef.ToList();
//linearCoef.ListCoef = dd.ListCoef.Where(w => w.coef_type == 1).ToList();
return linearCoef;
}
public float GetLinearRegression(DidiDBDetail detailData, DidiPerData fixData, LinearCoef LinearCoefData, int logisticRegression)
{
log.Info("GetLinearRegression data :{0}", DateTime.Now);
if (logisticRegression == 1 || logisticRegression == 3)
{
Dictionary<string, float > dicLinear = new Dictionary<string, float>();
string direction = logisticRegression == 1 ? "Increase" : "Decrease";
dicLinear = LinearCoefData.ListCoef.Where(w => w.promo_strgy == detailData.promo_strgy && w.keyword_cat == detailData.keyword_cat && w.direction == direction).Select(s => new { s.coef_name, s.coef }).ToDictionary(x => x.coef_name, x=>x.coef);
var ddd = LinearCoefData.ListCoef.Where(w => w.coef_type == 1).Select(s => s.coef).FirstOrDefault();
float f_per_p = dicLinear["click"] * fixData.click
+ dicLinear["imp"] * fixData.imp
+ dicLinear["conv"] * fixData.conv
+ dicLinear["roi"] * fixData.roi
+ dicLinear["imp_rank1"] * fixData.imp_rank1
+ dicLinear["pc_score"] * fixData.pc_score
+ dicLinear["ctr"] * fixData.ctr
+ dicLinear["ctr_ind"] * fixData.ctr_ind
+ dicLinear["cpc"] * fixData.cpc
+ dicLinear["cpc_ind"] * fixData.cpc_ind
+ dicLinear["d_spend_ind"] * fixData.d_spend_ind
+ dicLinear["cpc_limt_ind"] * fixData.cpc_limit_ind;
//float f_per_p = dicLinear["click"] * fixData.click;
//f_per_p = f_per_p + dicLinear["imp"] * fixData.imp;
//f_per_p = f_per_p + dicLinear["conv"] * fixData.conv;
//f_per_p = f_per_p + dicLinear["roi"] * fixData.roi;
//f_per_p = f_per_p + dicLinear["imp_rank1"] * fixData.imp_rank1;
// f_per_p = f_per_p + dicLinear["pc_score"] * fixData.pc_score;
//f_per_p = f_per_p + dicLinear["ctr"] * fixData.ctr;
//f_per_p = f_per_p + dicLinear["ctr_ind"] * fixData.ctr_ind;
//f_per_p = f_per_p + dicLinear["cpc"] * fixData.cpc;
//f_per_p = f_per_p + dicLinear["cpc_ind"] * fixData.cpc_ind;
//f_per_p = f_per_p + dicLinear["d_spend_ind"] * fixData.d_spend_ind;
//f_per_p = f_per_p + dicLinear["cpc_limt_ind"] * fixData.cpc_limit_ind;
log.Info("GetLinearRegression data end :{0}", DateTime.Now);
return f_per_p;
}
else
{
log.Info("GetLinearRegression data end nan :{0}", DateTime.Now);
return float.NaN;
}
}